{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# GAN Workflow Engine with the MedNIST Dataset\n",
    "\n",
    "The MONAI framework can be used to easily design, train, and evaluate generative adversarial networks.\n",
    "This notebook exemplifies using MONAI components to design and train a simple GAN model to reconstruct images of Hand CT scans.\n",
    "\n",
    "Read the [MONAI Mednist GAN Tutorial](https://github.com/Project-MONAI/MONAI/blob/master/examples/notebooks/mednist_GAN_tutorial.ipynb) for details about the network architecture and loss functions.\n",
    "\n",
    "**Table of Contents**\n",
    "\n",
    "1. Setup\n",
    "2. Initialize MONAI Components\n",
    "    * Create image transform chain\n",
    "    * Create dataset and dataloader\n",
    "    * Define generator and discriminator\n",
    "    * Create training handlers\n",
    "    * Create GanTrainer\n",
    "3. Run Training\n",
    "4. Evaluate Results\n",
    "\n",
    "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/Project-MONAI/MONAI/blob/master/examples/notebooks/mednist_GAN_workflow.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 1: Setup\n",
    "\n",
    "### Setup environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "Note: you may need to restart the kernel to use updated packages.\n"
    }
   ],
   "source": [
    "%pip install -qU \"monai[ignite]\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "Note: you may need to restart the kernel to use updated packages.\n"
    }
   ],
   "source": [
    "# temporarily need this, FIXME remove when d93c0a6 released\n",
    "%pip install -qU git+https://github.com/Project-MONAI/MONAI#egg=MONAI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "Note: you may need to restart the kernel to use updated packages.\n"
    }
   ],
   "source": [
    "%pip install -qU matplotlib\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Setup imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "MONAI version: 0.2.0+74.g8e5a53e\nPython version: 3.7.5 (default, Nov  7 2019, 10:50:52)  [GCC 8.3.0]\nNumpy version: 1.19.1\nPytorch version: 1.6.0\n\nOptional dependencies:\nPytorch Ignite version: 0.3.0\nNibabel version: NOT INSTALLED or UNKNOWN VERSION.\nscikit-image version: NOT INSTALLED or UNKNOWN VERSION.\nPillow version: 7.2.0\nTensorboard version: NOT INSTALLED or UNKNOWN VERSION.\n\nFor details about installing the optional dependencies, please visit:\n    https://docs.monai.io/en/latest/installation.html#installing-the-recommended-dependencies\n\n"
    }
   ],
   "source": [
    "import logging\n",
    "import os\n",
    "import shutil\n",
    "import sys\n",
    "import tempfile\n",
    "\n",
    "import IPython\n",
    "import matplotlib.pyplot as plt\n",
    "import torch\n",
    "\n",
    "from monai.apps import download_and_extract\n",
    "from monai.config import print_config\n",
    "from monai.data import CacheDataset, DataLoader\n",
    "from monai.engines import GanKeys, GanTrainer, default_make_latent\n",
    "from monai.handlers import CheckpointSaver, MetricLogger, StatsHandler\n",
    "from monai.networks import normal_init\n",
    "from monai.networks.nets import Discriminator, Generator\n",
    "from monai.transforms import (\n",
    "    AddChannelD,\n",
    "    Compose,\n",
    "    LoadPNGD,\n",
    "    RandFlipD,\n",
    "    RandRotateD,\n",
    "    RandZoomD,\n",
    "    ScaleIntensityD,\n",
    "    ToTensorD,\n",
    ")\n",
    "from monai.utils import set_determinism\n",
    "\n",
    "print_config()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Setup data directory\n",
    "\n",
    "You can specify a directory with the `MONAI_DATA_DIRECTORY` environment variable.  \n",
    "This allows you to save results and reuse downloads.  \n",
    "If not specified a temporary directory will be used."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "/home/bengorman/notebooks/\n"
    }
   ],
   "source": [
    "directory = os.environ.get(\"MONAI_DATA_DIRECTORY\")\n",
    "root_dir = tempfile.mkdtemp() if directory is None else directory\n",
    "print(root_dir)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Download dataset\n",
    "\n",
    "Downloads and extracts the dataset.\n",
    "\n",
    "The MedNIST dataset was gathered from several sets from [TCIA](https://wiki.cancerimagingarchive.net/display/Public/Data+Usage+Policies+and+Restrictions),\n",
    "[the RSNA Bone Age Challenge](http://rsnachallenges.cloudapp.net/competitions/4),\n",
    "and [the NIH Chest X-ray dataset](https://cloud.google.com/healthcare/docs/resources/public-datasets/nih-chest).\n",
    "\n",
    "The dataset is kindly made available by [Dr. Bradley J. Erickson M.D., Ph.D.](https://www.mayo.edu/research/labs/radiology-informatics/overview) (Department of Radiology, Mayo Clinic)\n",
    "under the Creative Commons [CC BY-SA 4.0 license](https://creativecommons.org/licenses/by-sa/4.0/).\n",
    "\n",
    "\n",
    "If you use the MedNIST dataset, please acknowledge the source, e.g.  \n",
    "https://github.com/Project-MONAI/MONAI/blob/master/examples/notebooks/mednist_tutorial.ipynb."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "file /home/bengorman/notebooks/MedNIST.tar.gz exists, skip downloading.\nextracted file /home/bengorman/notebooks/MedNIST exists, skip extracting.\n"
    }
   ],
   "source": [
    "resource = \"https://www.dropbox.com/s/5wwskxctvcxiuea/MedNIST.tar.gz?dl=1\"\n",
    "md5 = \"0bc7306e7427e00ad1c5526a6677552d\"\n",
    "\n",
    "compressed_file = os.path.join(root_dir, \"MedNIST.tar.gz\")\n",
    "data_dir = os.path.join(root_dir, \"MedNIST\")\n",
    "\n",
    "download_and_extract(resource, compressed_file, root_dir, md5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "hand_dir = os.path.join(data_dir, \"Hand\")\n",
    "training_datadict = [\n",
    "    {\"hand\": os.path.join(hand_dir, filename)} for filename in os.listdir(hand_dir)\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "[{'hand': '/home/bengorman/notebooks/MedNIST/Hand/003676.jpeg'}, {'hand': '/home/bengorman/notebooks/MedNIST/Hand/006548.jpeg'}, {'hand': '/home/bengorman/notebooks/MedNIST/Hand/002169.jpeg'}, {'hand': '/home/bengorman/notebooks/MedNIST/Hand/004081.jpeg'}, {'hand': '/home/bengorman/notebooks/MedNIST/Hand/004815.jpeg'}]\n"
    }
   ],
   "source": [
    "print(training_datadict[:5])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 2: Initialize MONAI components"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "logging.basicConfig(stream=sys.stdout, level=logging.INFO)\n",
    "set_determinism(0)\n",
    "device = torch.device(\"cuda:0\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create image transform chain\n",
    "\n",
    "Define the processing pipeline to convert saved disk images into usable Tensors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_transforms = Compose(\n",
    "    [\n",
    "        LoadPNGD(keys=[\"hand\"]),\n",
    "        AddChannelD(keys=[\"hand\"]),\n",
    "        ScaleIntensityD(keys=[\"hand\"]),\n",
    "        RandRotateD(keys=[\"hand\"], range_x=15, prob=0.5, keep_size=True),\n",
    "        RandFlipD(keys=[\"hand\"], spatial_axis=0, prob=0.5),\n",
    "        RandZoomD(keys=[\"hand\"], min_zoom=0.9, max_zoom=1.1, prob=0.5),\n",
    "        ToTensorD(keys=[\"hand\"]),\n",
    "    ]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create dataset and dataloader\n",
    "\n",
    "Hold data and present batches during training."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": "10000/10000 Load and cache transformed data:  [==============================]\n"
    }
   ],
   "source": [
    "real_dataset = CacheDataset(training_datadict, train_transforms)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "batch_size = 300\n",
    "real_dataloader = DataLoader(real_dataset, batch_size=batch_size, shuffle=True, num_workers=10)\n",
    "\n",
    "\n",
    "def prepare_batch(batchdata):\n",
    "    return batchdata[\"hand\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define generator and discriminator\n",
    "\n",
    "Load basic computer vision GAN networks from libraries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# define networks\n",
    "disc_net = Discriminator(\n",
    "    in_shape=(1, 64, 64),\n",
    "    channels=(8, 16, 32, 64, 1),\n",
    "    strides=(2, 2, 2, 2, 1),\n",
    "    num_res_units=1,\n",
    "    kernel_size=5,\n",
    ").to(device)\n",
    "\n",
    "latent_size = 64\n",
    "gen_net = Generator(\n",
    "    latent_shape=latent_size,\n",
    "    start_shape=(latent_size, 8, 8),\n",
    "    channels=[32, 16, 8, 1],\n",
    "    strides=[2, 2, 2, 1],\n",
    ")\n",
    "gen_net.conv.add_module(\"activation\", torch.nn.Sigmoid())\n",
    "gen_net = gen_net.to(device)\n",
    "\n",
    "# initialize both networks\n",
    "disc_net.apply(normal_init)\n",
    "gen_net.apply(normal_init)\n",
    "\n",
    "# define optimizors\n",
    "learning_rate = 2e-4\n",
    "betas = (0.5, 0.999)\n",
    "disc_opt = torch.optim.Adam(disc_net.parameters(), learning_rate, betas=betas)\n",
    "gen_opt = torch.optim.Adam(gen_net.parameters(), learning_rate, betas=betas)\n",
    "\n",
    "# define loss functions\n",
    "disc_loss_criterion = torch.nn.BCELoss()\n",
    "gen_loss_criterion = torch.nn.BCELoss()\n",
    "real_label = 1\n",
    "fake_label = 0\n",
    "\n",
    "\n",
    "def discriminator_loss(gen_images, real_images):\n",
    "    real = real_images.new_full((real_images.shape[0], 1), real_label)\n",
    "    gen = gen_images.new_full((gen_images.shape[0], 1), fake_label)\n",
    "\n",
    "    realloss = disc_loss_criterion(disc_net(real_images), real)\n",
    "    genloss = disc_loss_criterion(disc_net(gen_images.detach()), gen)\n",
    "\n",
    "    return (genloss + realloss) / 2\n",
    "\n",
    "\n",
    "def generator_loss(gen_images):\n",
    "    output = disc_net(gen_images)\n",
    "    cats = output.new_full(output.shape, real_label)\n",
    "    return gen_loss_criterion(output, cats)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create training handlers\n",
    "\n",
    "Perform operations during model training."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "metric_logger = MetricLogger(\n",
    "    loss_transform=lambda x: {GanKeys.GLOSS: x[GanKeys.GLOSS], GanKeys.DLOSS: x[GanKeys.DLOSS]},\n",
    "    metric_transform=lambda x: x,\n",
    ")\n",
    "\n",
    "handlers = [\n",
    "    StatsHandler(\n",
    "        name=\"batch_training_loss\",\n",
    "        output_transform=lambda x: {\n",
    "            GanKeys.GLOSS: x[GanKeys.GLOSS],\n",
    "            GanKeys.DLOSS: x[GanKeys.DLOSS],\n",
    "        },\n",
    "    ),\n",
    "    CheckpointSaver(\n",
    "        save_dir=os.path.join(root_dir, \"hand-gan\"),\n",
    "        save_dict={\"g_net\": gen_net, \"d_net\": disc_net},\n",
    "        save_interval=10,\n",
    "        save_final=True,\n",
    "        epoch_level=True,\n",
    "    ),\n",
    "    metric_logger,\n",
    "]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create GanTrainer\n",
    "\n",
    "MONAI Workflow engine for adversarial learning. The components come together here with the GanTrainer.\n",
    "\n",
    "Uses a training loop based on Goodfellow et al. 2014 https://arxiv.org/abs/1406.266. \n",
    "\n",
    "```\n",
    "Training Loop: for each batch of data size m\n",
    "        1. Generate m fakes from random latent codes.\n",
    "        2. Update D with these fakes and current batch reals, repeated d_train_steps times.\n",
    "        3. Generate m fakes from new random latent codes.\n",
    "        4. Update generator with these fakes using discriminator feedback.\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "disc_train_steps = 5\n",
    "num_epochs = 50\n",
    "\n",
    "trainer = GanTrainer(\n",
    "    device,\n",
    "    num_epochs,\n",
    "    real_dataloader,\n",
    "    gen_net,\n",
    "    gen_opt,\n",
    "    generator_loss,\n",
    "    disc_net,\n",
    "    disc_opt,\n",
    "    discriminator_loss,\n",
    "    d_prepare_batch=prepare_batch,\n",
    "    d_train_steps=disc_train_steps,\n",
    "    g_update_latents=True,\n",
    "    latent_shape=latent_size,\n",
    "    key_train_metric=None,\n",
    "    train_handlers=handlers,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 3: Start Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true,
    "pycharm": {
     "is_executing": true
    },
    "tags": [
     "outputPrepend"
    ]
   },
   "outputs": [],
   "source": [
    "trainer.run()\n",
    "IPython.display.clear_output()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Evaluate Results\n",
    "\n",
    "Examine G and D loss curves for collapse."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "g_loss = [loss[GanKeys.GLOSS] for loss in metric_logger.loss]\n",
    "d_loss = [loss[GanKeys.DLOSS] for loss in metric_logger.loss]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true,
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 864x360 with 1 Axes>",
      "image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n<!-- Created with matplotlib (https://matplotlib.org/) -->\n<svg height=\"302.878125pt\" version=\"1.1\" viewBox=\"0 0 715.061203 302.878125\" width=\"715.061203pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n <metadata>\n  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n   <cc:Work>\n    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n    <dc:date>2020-08-05T18:23:17.519994</dc:date>\n    <dc:format>image/svg+xml</dc:format>\n    <dc:creator>\n     <cc:Agent>\n      <dc:title>Matplotlib v3.3.0, https://matplotlib.org/</dc:title>\n     </cc:Agent>\n    </dc:creator>\n   </cc:Work>\n  </rdf:RDF>\n </metadata>\n <defs>\n  <style type=\"text/css\">*{stroke-linecap:butt;stroke-linejoin:round;}</style>\n </defs>\n <g id=\"figure_1\">\n  <g id=\"patch_1\">\n   <path d=\"M 0 302.878125 \nL 715.061203 302.878125 \nL 715.061203 0 \nL 0 0 \nz\n\" style=\"fill:none;\"/>\n  </g>\n  <g id=\"axes_1\">\n   <g id=\"patch_2\">\n    <path d=\"M 37.7 279 \nL 707.3 279 \nL 707.3 7.2 \nL 37.7 7.2 \nz\n\" style=\"fill:#ffffff;\"/>\n   </g>\n   <g id=\"matplotlib.axis_1\">\n    <g id=\"xtick_1\">\n     <g id=\"line2d_1\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 68.136364 279 \nL 68.136364 7.2 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_2\">\n      <defs>\n       <path d=\"M 0 0 \nL 0 3.5 \n\" id=\"m72c718b4fd\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n      </defs>\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"68.136364\" xlink:href=\"#m72c718b4fd\" y=\"279\"/>\n      </g>\n     </g>\n     <g id=\"text_1\">\n      <!-- 0 -->\n      <g transform=\"translate(64.955114 293.598437)scale(0.1 -0.1)\">\n       <defs>\n        <path d=\"M 31.78125 66.40625 \nQ 24.171875 66.40625 20.328125 58.90625 \nQ 16.5 51.421875 16.5 36.375 \nQ 16.5 21.390625 20.328125 13.890625 \nQ 24.171875 6.390625 31.78125 6.390625 \nQ 39.453125 6.390625 43.28125 13.890625 \nQ 47.125 21.390625 47.125 36.375 \nQ 47.125 51.421875 43.28125 58.90625 \nQ 39.453125 66.40625 31.78125 66.40625 \nz\nM 31.78125 74.21875 \nQ 44.046875 74.21875 50.515625 64.515625 \nQ 56.984375 54.828125 56.984375 36.375 \nQ 56.984375 17.96875 50.515625 8.265625 \nQ 44.046875 -1.421875 31.78125 -1.421875 \nQ 19.53125 -1.421875 13.0625 8.265625 \nQ 6.59375 17.96875 6.59375 36.375 \nQ 6.59375 54.828125 13.0625 64.515625 \nQ 19.53125 74.21875 31.78125 74.21875 \nz\n\" id=\"DejaVuSans-48\"/>\n       </defs>\n       <use xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"xtick_2\">\n     <g id=\"line2d_3\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 157.707769 279 \nL 157.707769 7.2 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_4\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"157.707769\" xlink:href=\"#m72c718b4fd\" y=\"279\"/>\n      </g>\n     </g>\n     <g id=\"text_2\">\n      <!-- 250 -->\n      <g transform=\"translate(148.164019 293.598437)scale(0.1 -0.1)\">\n       <defs>\n        <path d=\"M 19.1875 8.296875 \nL 53.609375 8.296875 \nL 53.609375 0 \nL 7.328125 0 \nL 7.328125 8.296875 \nQ 12.9375 14.109375 22.625 23.890625 \nQ 32.328125 33.6875 34.8125 36.53125 \nQ 39.546875 41.84375 41.421875 45.53125 \nQ 43.3125 49.21875 43.3125 52.78125 \nQ 43.3125 58.59375 39.234375 62.25 \nQ 35.15625 65.921875 28.609375 65.921875 \nQ 23.96875 65.921875 18.8125 64.3125 \nQ 13.671875 62.703125 7.8125 59.421875 \nL 7.8125 69.390625 \nQ 13.765625 71.78125 18.9375 73 \nQ 24.125 74.21875 28.421875 74.21875 \nQ 39.75 74.21875 46.484375 68.546875 \nQ 53.21875 62.890625 53.21875 53.421875 \nQ 53.21875 48.921875 51.53125 44.890625 \nQ 49.859375 40.875 45.40625 35.40625 \nQ 44.1875 33.984375 37.640625 27.21875 \nQ 31.109375 20.453125 19.1875 8.296875 \nz\n\" id=\"DejaVuSans-50\"/>\n        <path d=\"M 10.796875 72.90625 \nL 49.515625 72.90625 \nL 49.515625 64.59375 \nL 19.828125 64.59375 \nL 19.828125 46.734375 \nQ 21.96875 47.46875 24.109375 47.828125 \nQ 26.265625 48.1875 28.421875 48.1875 \nQ 40.625 48.1875 47.75 41.5 \nQ 54.890625 34.8125 54.890625 23.390625 \nQ 54.890625 11.625 47.5625 5.09375 \nQ 40.234375 -1.421875 26.90625 -1.421875 \nQ 22.3125 -1.421875 17.546875 -0.640625 \nQ 12.796875 0.140625 7.71875 1.703125 \nL 7.71875 11.625 \nQ 12.109375 9.234375 16.796875 8.0625 \nQ 21.484375 6.890625 26.703125 6.890625 \nQ 35.15625 6.890625 40.078125 11.328125 \nQ 45.015625 15.765625 45.015625 23.390625 \nQ 45.015625 31 40.078125 35.4375 \nQ 35.15625 39.890625 26.703125 39.890625 \nQ 22.75 39.890625 18.8125 39.015625 \nQ 14.890625 38.140625 10.796875 36.28125 \nz\n\" id=\"DejaVuSans-53\"/>\n       </defs>\n       <use xlink:href=\"#DejaVuSans-50\"/>\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-53\"/>\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"xtick_3\">\n     <g id=\"line2d_5\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 247.279175 279 \nL 247.279175 7.2 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_6\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"247.279175\" xlink:href=\"#m72c718b4fd\" y=\"279\"/>\n      </g>\n     </g>\n     <g id=\"text_3\">\n      <!-- 500 -->\n      <g transform=\"translate(237.735425 293.598437)scale(0.1 -0.1)\">\n       <use xlink:href=\"#DejaVuSans-53\"/>\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"xtick_4\">\n     <g id=\"line2d_7\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 336.850581 279 \nL 336.850581 7.2 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_8\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"336.850581\" xlink:href=\"#m72c718b4fd\" y=\"279\"/>\n      </g>\n     </g>\n     <g id=\"text_4\">\n      <!-- 750 -->\n      <g transform=\"translate(327.306831 293.598437)scale(0.1 -0.1)\">\n       <defs>\n        <path d=\"M 8.203125 72.90625 \nL 55.078125 72.90625 \nL 55.078125 68.703125 \nL 28.609375 0 \nL 18.3125 0 \nL 43.21875 64.59375 \nL 8.203125 64.59375 \nz\n\" id=\"DejaVuSans-55\"/>\n       </defs>\n       <use xlink:href=\"#DejaVuSans-55\"/>\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-53\"/>\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"xtick_5\">\n     <g id=\"line2d_9\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 426.421986 279 \nL 426.421986 7.2 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_10\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"426.421986\" xlink:href=\"#m72c718b4fd\" y=\"279\"/>\n      </g>\n     </g>\n     <g id=\"text_5\">\n      <!-- 1000 -->\n      <g transform=\"translate(413.696986 293.598437)scale(0.1 -0.1)\">\n       <defs>\n        <path d=\"M 12.40625 8.296875 \nL 28.515625 8.296875 \nL 28.515625 63.921875 \nL 10.984375 60.40625 \nL 10.984375 69.390625 \nL 28.421875 72.90625 \nL 38.28125 72.90625 \nL 38.28125 8.296875 \nL 54.390625 8.296875 \nL 54.390625 0 \nL 12.40625 0 \nz\n\" id=\"DejaVuSans-49\"/>\n       </defs>\n       <use xlink:href=\"#DejaVuSans-49\"/>\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-48\"/>\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-48\"/>\n       <use x=\"190.869141\" xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"xtick_6\">\n     <g id=\"line2d_11\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 515.993392 279 \nL 515.993392 7.2 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_12\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"515.993392\" xlink:href=\"#m72c718b4fd\" y=\"279\"/>\n      </g>\n     </g>\n     <g id=\"text_6\">\n      <!-- 1250 -->\n      <g transform=\"translate(503.268392 293.598437)scale(0.1 -0.1)\">\n       <use xlink:href=\"#DejaVuSans-49\"/>\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-50\"/>\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-53\"/>\n       <use x=\"190.869141\" xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"xtick_7\">\n     <g id=\"line2d_13\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 605.564797 279 \nL 605.564797 7.2 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_14\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"605.564797\" xlink:href=\"#m72c718b4fd\" y=\"279\"/>\n      </g>\n     </g>\n     <g id=\"text_7\">\n      <!-- 1500 -->\n      <g transform=\"translate(592.839797 293.598437)scale(0.1 -0.1)\">\n       <use xlink:href=\"#DejaVuSans-49\"/>\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-53\"/>\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-48\"/>\n       <use x=\"190.869141\" xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"xtick_8\">\n     <g id=\"line2d_15\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 695.136203 279 \nL 695.136203 7.2 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_16\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"695.136203\" xlink:href=\"#m72c718b4fd\" y=\"279\"/>\n      </g>\n     </g>\n     <g id=\"text_8\">\n      <!-- 1750 -->\n      <g transform=\"translate(682.411203 293.598437)scale(0.1 -0.1)\">\n       <use xlink:href=\"#DejaVuSans-49\"/>\n       <use x=\"63.623047\" xlink:href=\"#DejaVuSans-55\"/>\n       <use x=\"127.246094\" xlink:href=\"#DejaVuSans-53\"/>\n       <use x=\"190.869141\" xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"matplotlib.axis_2\">\n    <g id=\"ytick_1\">\n     <g id=\"line2d_17\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 261.083192 \nL 707.3 261.083192 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_18\">\n      <defs>\n       <path d=\"M 0 0 \nL -3.5 0 \n\" id=\"m35398c0c28\" style=\"stroke:#000000;stroke-width:0.8;\"/>\n      </defs>\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"37.7\" xlink:href=\"#m35398c0c28\" y=\"261.083192\"/>\n      </g>\n     </g>\n     <g id=\"text_9\">\n      <!-- $\\mathdefault{10^{-2}}$ -->\n      <g transform=\"translate(7.2 264.882411)scale(0.1 -0.1)\">\n       <defs>\n        <path d=\"M 10.59375 35.5 \nL 73.1875 35.5 \nL 73.1875 27.203125 \nL 10.59375 27.203125 \nz\n\" id=\"DejaVuSans-8722\"/>\n       </defs>\n       <use transform=\"translate(0 0.765625)\" xlink:href=\"#DejaVuSans-49\"/>\n       <use transform=\"translate(63.623047 0.765625)\" xlink:href=\"#DejaVuSans-48\"/>\n       <use transform=\"translate(128.203125 39.046875)scale(0.7)\" xlink:href=\"#DejaVuSans-8722\"/>\n       <use transform=\"translate(186.855469 39.046875)scale(0.7)\" xlink:href=\"#DejaVuSans-50\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_2\">\n     <g id=\"line2d_19\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 179.812202 \nL 707.3 179.812202 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_20\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"37.7\" xlink:href=\"#m35398c0c28\" y=\"179.812202\"/>\n      </g>\n     </g>\n     <g id=\"text_10\">\n      <!-- $\\mathdefault{10^{-1}}$ -->\n      <g transform=\"translate(7.2 183.61142)scale(0.1 -0.1)\">\n       <use transform=\"translate(0 0.684375)\" xlink:href=\"#DejaVuSans-49\"/>\n       <use transform=\"translate(63.623047 0.684375)\" xlink:href=\"#DejaVuSans-48\"/>\n       <use transform=\"translate(128.203125 38.965625)scale(0.7)\" xlink:href=\"#DejaVuSans-8722\"/>\n       <use transform=\"translate(186.855469 38.965625)scale(0.7)\" xlink:href=\"#DejaVuSans-49\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_3\">\n     <g id=\"line2d_21\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 98.541211 \nL 707.3 98.541211 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_22\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"37.7\" xlink:href=\"#m35398c0c28\" y=\"98.541211\"/>\n      </g>\n     </g>\n     <g id=\"text_11\">\n      <!-- $\\mathdefault{10^{0}}$ -->\n      <g transform=\"translate(13.1 102.34043)scale(0.1 -0.1)\">\n       <use transform=\"translate(0 0.765625)\" xlink:href=\"#DejaVuSans-49\"/>\n       <use transform=\"translate(63.623047 0.765625)\" xlink:href=\"#DejaVuSans-48\"/>\n       <use transform=\"translate(128.203125 39.046875)scale(0.7)\" xlink:href=\"#DejaVuSans-48\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_4\">\n     <g id=\"line2d_23\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 17.270221 \nL 707.3 17.270221 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_24\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.8;\" x=\"37.7\" xlink:href=\"#m35398c0c28\" y=\"17.270221\"/>\n      </g>\n     </g>\n     <g id=\"text_12\">\n      <!-- $\\mathdefault{10^{1}}$ -->\n      <g transform=\"translate(13.1 21.06944)scale(0.1 -0.1)\">\n       <use transform=\"translate(0 0.684375)\" xlink:href=\"#DejaVuSans-49\"/>\n       <use transform=\"translate(63.623047 0.684375)\" xlink:href=\"#DejaVuSans-48\"/>\n       <use transform=\"translate(128.203125 38.965625)scale(0.7)\" xlink:href=\"#DejaVuSans-49\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_5\">\n     <g id=\"line2d_25\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 273.672227 \nL 707.3 273.672227 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_26\">\n      <defs>\n       <path d=\"M 0 0 \nL -2 0 \n\" id=\"m670a3e184a\" style=\"stroke:#000000;stroke-width:0.6;\"/>\n      </defs>\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"273.672227\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_6\">\n     <g id=\"line2d_27\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 268.959164 \nL 707.3 268.959164 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_28\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"268.959164\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_7\">\n     <g id=\"line2d_29\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 264.801948 \nL 707.3 264.801948 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_30\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"264.801948\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_8\">\n     <g id=\"line2d_31\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 236.618186 \nL 707.3 236.618186 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_32\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"236.618186\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_9\">\n     <g id=\"line2d_33\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 222.307075 \nL 707.3 222.307075 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_34\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"222.307075\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_10\">\n     <g id=\"line2d_35\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 212.15318 \nL 707.3 212.15318 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_36\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"212.15318\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_11\">\n     <g id=\"line2d_37\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 204.277207 \nL 707.3 204.277207 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_38\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"204.277207\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_12\">\n     <g id=\"line2d_39\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 197.842069 \nL 707.3 197.842069 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_40\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"197.842069\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_13\">\n     <g id=\"line2d_41\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 192.401237 \nL 707.3 192.401237 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_42\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"192.401237\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_14\">\n     <g id=\"line2d_43\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 187.688174 \nL 707.3 187.688174 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_44\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"187.688174\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_15\">\n     <g id=\"line2d_45\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 183.530958 \nL 707.3 183.530958 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_46\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"183.530958\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_16\">\n     <g id=\"line2d_47\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 155.347196 \nL 707.3 155.347196 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_48\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"155.347196\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_17\">\n     <g id=\"line2d_49\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 141.036085 \nL 707.3 141.036085 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_50\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"141.036085\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_18\">\n     <g id=\"line2d_51\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 130.88219 \nL 707.3 130.88219 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_52\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"130.88219\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_19\">\n     <g id=\"line2d_53\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 123.006217 \nL 707.3 123.006217 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_54\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"123.006217\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_20\">\n     <g id=\"line2d_55\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 116.571079 \nL 707.3 116.571079 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_56\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"116.571079\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_21\">\n     <g id=\"line2d_57\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 111.130247 \nL 707.3 111.130247 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_58\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"111.130247\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_22\">\n     <g id=\"line2d_59\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 106.417184 \nL 707.3 106.417184 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_60\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"106.417184\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_23\">\n     <g id=\"line2d_61\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 102.259968 \nL 707.3 102.259968 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_62\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"102.259968\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_24\">\n     <g id=\"line2d_63\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 74.076205 \nL 707.3 74.076205 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_64\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"74.076205\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_25\">\n     <g id=\"line2d_65\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 59.765094 \nL 707.3 59.765094 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_66\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"59.765094\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_26\">\n     <g id=\"line2d_67\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 49.6112 \nL 707.3 49.6112 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_68\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"49.6112\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_27\">\n     <g id=\"line2d_69\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 41.735227 \nL 707.3 41.735227 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_70\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"41.735227\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_28\">\n     <g id=\"line2d_71\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 35.300089 \nL 707.3 35.300089 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_72\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"35.300089\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_29\">\n     <g id=\"line2d_73\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 29.859257 \nL 707.3 29.859257 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_74\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"29.859257\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_30\">\n     <g id=\"line2d_75\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 25.146194 \nL 707.3 25.146194 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_76\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"25.146194\"/>\n      </g>\n     </g>\n    </g>\n    <g id=\"ytick_31\">\n     <g id=\"line2d_77\">\n      <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 37.7 20.988978 \nL 707.3 20.988978 \n\" style=\"fill:none;stroke:#b0b0b0;stroke-linecap:square;stroke-width:0.8;\"/>\n     </g>\n     <g id=\"line2d_78\">\n      <g>\n       <use style=\"stroke:#000000;stroke-width:0.6;\" x=\"37.7\" xlink:href=\"#m670a3e184a\" y=\"20.988978\"/>\n      </g>\n     </g>\n    </g>\n   </g>\n   <g id=\"line2d_79\">\n    <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 68.136364 105.110354 \nL 68.852935 82.969369 \nL 69.569506 61.923686 \nL 69.927792 54.200863 \nL 70.286077 49.248352 \nL 71.002649 43.811341 \nL 71.360934 42.048589 \nL 71.71922 39.475491 \nL 72.077505 39.003769 \nL 72.435791 37.633524 \nL 72.794077 37.783172 \nL 73.152362 36.290975 \nL 73.510648 37.535974 \nL 73.868934 35.986999 \nL 74.227219 37.105135 \nL 74.585505 37.703375 \nL 74.94379 32.809744 \nL 75.302076 35.617094 \nL 75.660362 37.376165 \nL 76.018647 35.89365 \nL 76.376933 33.421353 \nL 76.735219 33.661656 \nL 77.093504 36.408283 \nL 77.45179 35.330508 \nL 77.810075 40.109054 \nL 78.168361 37.911588 \nL 78.526647 33.088099 \nL 78.884932 33.194541 \nL 79.243218 32.69096 \nL 79.601504 26.884131 \nL 80.318075 29.218458 \nL 80.67636 32.460063 \nL 81.392932 30.992012 \nL 81.751217 29.822374 \nL 82.109503 32.953227 \nL 82.467789 20.103953 \nL 82.826074 30.440749 \nL 83.18436 28.809075 \nL 83.542645 35.408839 \nL 83.900931 19.554545 \nL 84.259217 28.256383 \nL 84.617502 34.09185 \nL 84.975788 31.910856 \nL 85.334074 36.506636 \nL 85.692359 36.650286 \nL 86.050645 31.3934 \nL 86.40893 33.1878 \nL 86.767216 38.518763 \nL 87.125502 34.732839 \nL 87.483787 38.886213 \nL 87.842073 56.07983 \nL 88.200358 37.644308 \nL 88.558644 40.570799 \nL 88.91693 42.443466 \nL 89.275215 41.534081 \nL 89.633501 42.933659 \nL 90.350072 42.679567 \nL 90.708358 36.615427 \nL 91.066643 40.580972 \nL 91.424929 42.451637 \nL 91.783215 42.139779 \nL 92.1415 44.779547 \nL 92.499786 44.857359 \nL 92.858072 39.585825 \nL 93.216357 42.243261 \nL 93.574643 41.65755 \nL 93.932928 73.760757 \nL 94.291214 48.651261 \nL 94.6495 62.257312 \nL 95.007785 57.856615 \nL 95.366071 50.011549 \nL 95.724357 47.566185 \nL 96.082642 51.18656 \nL 96.440928 51.040965 \nL 96.799213 48.636209 \nL 97.157499 50.090365 \nL 97.515785 50.110184 \nL 97.87407 45.60559 \nL 98.232356 53.512727 \nL 98.590642 52.548008 \nL 98.948927 49.103321 \nL 99.307213 47.843745 \nL 99.665498 54.054562 \nL 100.38207 48.785477 \nL 100.740355 55.298791 \nL 101.098641 48.064817 \nL 101.456927 51.584017 \nL 101.815212 48.105793 \nL 102.173498 68.870284 \nL 102.531783 62.588266 \nL 102.890069 52.008107 \nL 103.248355 58.200955 \nL 103.60664 45.455599 \nL 103.964926 49.686462 \nL 104.323212 56.17547 \nL 104.681497 53.056075 \nL 105.039783 51.381766 \nL 105.398068 53.002661 \nL 105.756354 47.298801 \nL 106.472925 57.898547 \nL 106.831211 50.77853 \nL 107.189496 57.787662 \nL 107.547782 55.063029 \nL 107.906068 54.027725 \nL 108.264353 48.740322 \nL 108.622639 46.924789 \nL 108.980925 55.36286 \nL 109.33921 51.247444 \nL 109.697496 49.080434 \nL 110.414067 52.736266 \nL 110.772353 50.977338 \nL 111.130638 59.578467 \nL 111.488924 82.297426 \nL 111.84721 47.29568 \nL 112.205495 53.475673 \nL 112.563781 55.41477 \nL 112.922066 53.094246 \nL 113.280352 48.215651 \nL 113.638638 54.097021 \nL 113.996923 50.721211 \nL 114.355209 49.354365 \nL 114.713495 49.618711 \nL 115.07178 51.995244 \nL 115.430066 51.380244 \nL 115.788351 52.182246 \nL 116.146637 49.566081 \nL 116.504923 50.727377 \nL 116.863208 53.532495 \nL 117.221494 47.047358 \nL 117.57978 48.313801 \nL 117.938065 47.395671 \nL 118.296351 50.714772 \nL 118.654636 50.691769 \nL 119.012922 46.681984 \nL 119.371208 49.058047 \nL 119.729493 47.663084 \nL 120.087779 48.865064 \nL 120.446065 51.935768 \nL 120.80435 48.720386 \nL 121.162636 49.529201 \nL 121.520921 54.136904 \nL 121.879207 46.430133 \nL 122.237493 49.281458 \nL 122.595778 46.411728 \nL 122.954064 50.9517 \nL 123.31235 42.384662 \nL 123.670635 50.472538 \nL 124.028921 49.323313 \nL 124.387206 51.629738 \nL 124.745492 50.883733 \nL 125.103778 53.547086 \nL 125.462063 48.159696 \nL 125.820349 47.408544 \nL 126.53692 52.437825 \nL 126.895206 50.207096 \nL 127.253491 54.934416 \nL 127.611777 51.972845 \nL 127.970063 50.988521 \nL 128.328348 64.02667 \nL 129.044919 48.328976 \nL 129.403205 51.068935 \nL 129.761491 51.542737 \nL 130.119776 58.951391 \nL 130.478062 57.179748 \nL 130.836348 51.241913 \nL 131.552919 55.820235 \nL 131.911204 55.320583 \nL 132.26949 56.292857 \nL 132.627776 53.097337 \nL 132.986061 56.57601 \nL 133.344347 49.501398 \nL 133.702633 62.087225 \nL 134.060918 53.900585 \nL 134.419204 50.039012 \nL 134.777489 49.562905 \nL 135.135775 49.9709 \nL 135.494061 51.06364 \nL 135.852346 54.464921 \nL 136.210632 53.356966 \nL 136.927203 42.709299 \nL 137.285489 50.537958 \nL 137.643774 54.94199 \nL 138.00206 48.894123 \nL 138.360346 50.922625 \nL 139.076917 52.457867 \nL 139.435203 50.790174 \nL 139.793488 50.744126 \nL 140.151774 51.485626 \nL 140.510059 46.941937 \nL 140.868345 51.430914 \nL 141.226631 49.714338 \nL 141.584916 53.154453 \nL 141.943202 46.075785 \nL 142.301488 51.906544 \nL 142.659773 54.40507 \nL 143.018059 45.527631 \nL 143.376344 49.673649 \nL 143.73463 48.732778 \nL 144.092916 52.276161 \nL 144.451201 49.415247 \nL 144.809487 50.297865 \nL 145.167772 48.058008 \nL 145.526058 49.715925 \nL 145.884344 55.51364 \nL 146.242629 50.83412 \nL 146.600915 51.700326 \nL 146.959201 49.934261 \nL 147.317486 51.130485 \nL 147.675772 50.634105 \nL 148.392343 53.768799 \nL 148.750629 51.403774 \nL 149.108914 51.284448 \nL 149.825486 57.617373 \nL 150.183771 59.183075 \nL 150.900342 48.847482 \nL 151.258628 50.763807 \nL 151.616914 49.428481 \nL 151.975199 55.627614 \nL 152.333485 47.241195 \nL 152.691771 52.446909 \nL 153.050056 59.903159 \nL 153.408342 61.293234 \nL 153.766627 51.440163 \nL 154.124913 53.267364 \nL 154.483199 50.347265 \nL 155.19977 54.008366 \nL 155.558056 49.353003 \nL 156.274627 54.300516 \nL 156.632912 52.245376 \nL 156.991198 60.449013 \nL 157.349484 19.801227 \nL 157.707769 55.843998 \nL 158.066055 57.829921 \nL 158.424341 58.44884 \nL 158.782626 55.34588 \nL 159.140912 54.540163 \nL 159.857483 56.32981 \nL 160.215769 56.049444 \nL 160.574054 56.719469 \nL 161.290626 53.929673 \nL 161.648911 57.250576 \nL 162.007197 57.085501 \nL 162.365482 53.034951 \nL 162.723768 60.775667 \nL 163.082054 54.42521 \nL 163.440339 52.919202 \nL 163.798625 59.272804 \nL 164.15691 56.566247 \nL 164.515196 61.797026 \nL 164.873482 54.481665 \nL 165.231767 55.94343 \nL 165.590053 60.646177 \nL 165.948339 59.929665 \nL 166.306624 55.288256 \nL 166.66491 56.880335 \nL 167.023195 57.739502 \nL 167.381481 54.620124 \nL 167.739767 52.926934 \nL 168.098052 57.919458 \nL 168.456338 57.415878 \nL 168.814624 59.116611 \nL 169.172909 62.083109 \nL 169.531195 40.724382 \nL 169.88948 52.484682 \nL 170.247766 54.603564 \nL 170.606052 62.978619 \nL 170.964337 52.597936 \nL 171.322623 58.396486 \nL 171.680909 57.803685 \nL 172.039194 61.172009 \nL 172.39748 44.942836 \nL 172.755765 55.96752 \nL 173.114051 52.631384 \nL 173.472337 55.009657 \nL 173.830622 61.513622 \nL 174.547194 55.440152 \nL 174.905479 56.272902 \nL 175.263765 54.027305 \nL 175.62205 59.771002 \nL 175.980336 58.640851 \nL 176.338622 55.511328 \nL 176.696907 54.509708 \nL 177.055193 63.839485 \nL 177.413479 58.721622 \nL 177.771764 57.996336 \nL 178.13005 57.584688 \nL 178.488335 58.632697 \nL 178.846621 52.657301 \nL 179.204907 56.125903 \nL 179.563192 49.337372 \nL 179.921478 57.552531 \nL 180.279763 48.963931 \nL 180.638049 62.535452 \nL 180.996335 66.865309 \nL 181.35462 61.903749 \nL 181.712906 67.290076 \nL 182.787763 58.868143 \nL 183.146048 58.579242 \nL 183.504334 56.429359 \nL 183.86262 52.120759 \nL 184.220905 58.554197 \nL 184.579191 68.58393 \nL 184.937477 56.513857 \nL 185.295762 58.882418 \nL 185.654048 55.106273 \nL 186.012333 62.139891 \nL 186.370619 47.841893 \nL 186.728905 63.166544 \nL 187.445476 56.141245 \nL 187.803762 56.775304 \nL 188.162047 53.853014 \nL 188.520333 49.543128 \nL 188.878618 76.59738 \nL 189.236904 63.389565 \nL 189.59519 65.456766 \nL 189.953475 62.70256 \nL 190.311761 62.213225 \nL 190.670047 68.204702 \nL 191.028332 66.892335 \nL 191.386618 62.516218 \nL 191.744903 54.68745 \nL 192.103189 64.199567 \nL 192.461475 55.617422 \nL 193.178046 76.563324 \nL 193.536332 62.14946 \nL 193.894617 63.246125 \nL 194.252903 55.549649 \nL 194.611188 83.231291 \nL 194.969474 52.37308 \nL 195.32776 85.459208 \nL 195.686045 76.783507 \nL 196.402617 69.157219 \nL 196.760902 68.313176 \nL 197.119188 61.968578 \nL 197.477473 66.341721 \nL 197.835759 64.61548 \nL 198.194045 64.888479 \nL 198.55233 65.588713 \nL 198.910616 67.662015 \nL 199.627187 62.396779 \nL 199.985473 68.558032 \nL 200.343758 59.847814 \nL 201.06033 66.842075 \nL 201.418615 74.275035 \nL 201.776901 61.954823 \nL 202.135186 69.635435 \nL 202.851758 60.287042 \nL 203.210043 62.279463 \nL 203.568329 60.161473 \nL 203.926615 65.269442 \nL 204.2849 64.194326 \nL 204.643186 70.234809 \nL 205.001471 61.472039 \nL 205.359757 61.323335 \nL 205.718043 54.867962 \nL 206.076328 81.752736 \nL 206.434614 68.283166 \nL 206.7929 64.79969 \nL 207.509471 59.939073 \nL 207.867756 60.189071 \nL 208.226042 57.327117 \nL 208.584328 69.99737 \nL 208.942613 62.403123 \nL 209.300899 65.449318 \nL 209.659185 55.612022 \nL 210.01747 55.779249 \nL 210.734041 66.113851 \nL 211.092327 65.475914 \nL 211.808898 64.993814 \nL 212.167184 60.762548 \nL 212.52547 87.516587 \nL 212.883755 76.079094 \nL 213.600326 63.470928 \nL 213.958612 67.813269 \nL 214.316898 75.204338 \nL 214.675183 67.781016 \nL 215.033469 71.580445 \nL 215.391755 66.179608 \nL 215.75004 66.1842 \nL 216.108326 66.387886 \nL 216.466611 65.461256 \nL 216.824897 74.349568 \nL 217.183183 70.741381 \nL 217.541468 64.640411 \nL 217.899754 73.746464 \nL 218.258039 66.891092 \nL 218.616325 62.890057 \nL 218.974611 64.076954 \nL 219.332896 66.700857 \nL 219.691182 66.760901 \nL 220.049468 62.519014 \nL 220.407753 60.039922 \nL 220.766039 60.38528 \nL 221.124324 67.347418 \nL 221.48261 62.012086 \nL 221.840896 67.218852 \nL 222.199181 63.22619 \nL 223.274038 72.130491 \nL 223.632324 59.239644 \nL 223.990609 66.51767 \nL 224.348895 71.179243 \nL 224.707181 71.215696 \nL 225.065466 59.172101 \nL 225.782038 68.031508 \nL 226.140323 69.049977 \nL 226.856894 58.929603 \nL 227.21518 61.74967 \nL 227.573466 53.434093 \nL 227.931751 69.448997 \nL 228.290037 61.096723 \nL 228.648323 61.451172 \nL 229.006608 65.479733 \nL 229.364894 63.758674 \nL 230.081465 67.94101 \nL 230.439751 36.38133 \nL 230.798036 63.114835 \nL 231.156322 66.608605 \nL 231.514608 66.004158 \nL 231.872893 62.214574 \nL 232.231179 64.156154 \nL 232.589464 64.022743 \nL 233.306036 65.692466 \nL 233.664321 64.295983 \nL 234.022607 64.08614 \nL 234.380893 61.915293 \nL 234.739178 68.238168 \nL 235.097464 63.54628 \nL 235.455749 67.614908 \nL 235.814035 62.518529 \nL 236.172321 64.314445 \nL 236.530606 67.055593 \nL 236.888892 67.883632 \nL 237.247177 65.90278 \nL 237.605463 71.411855 \nL 237.963749 66.47925 \nL 238.322034 64.850566 \nL 238.68032 61.272833 \nL 239.038606 65.250271 \nL 239.396891 65.845397 \nL 239.755177 65.167204 \nL 240.113462 69.57456 \nL 240.471748 65.927315 \nL 240.830034 68.93273 \nL 241.188319 63.208921 \nL 241.546605 65.027433 \nL 241.904891 72.81423 \nL 242.263176 64.2145 \nL 242.621462 60.922109 \nL 242.979747 61.753388 \nL 243.338033 69.48614 \nL 243.696319 63.367515 \nL 244.054604 66.204437 \nL 244.41289 66.240082 \nL 244.771176 71.377841 \nL 245.129461 64.366204 \nL 245.487747 71.489497 \nL 245.846032 59.68066 \nL 246.204318 56.479149 \nL 246.562604 60.844882 \nL 246.920889 68.543885 \nL 247.279175 55.956063 \nL 247.995746 69.515479 \nL 248.354032 68.162277 \nL 248.712317 68.037532 \nL 249.070603 68.50288 \nL 249.428889 64.581582 \nL 249.787174 70.107004 \nL 250.503746 67.03812 \nL 250.862031 60.52811 \nL 251.220317 65.758542 \nL 251.578602 63.797214 \nL 251.936888 66.634917 \nL 252.295174 65.881995 \nL 252.653459 67.990159 \nL 253.011745 72.635368 \nL 253.37003 62.772727 \nL 253.728316 64.239334 \nL 254.086602 60.995762 \nL 254.803173 58.26632 \nL 255.161459 56.359891 \nL 255.519744 61.504571 \nL 255.87803 48.501233 \nL 256.236315 60.607442 \nL 256.594601 36.864935 \nL 256.952887 71.343604 \nL 257.311172 66.434552 \nL 257.669458 64.219559 \nL 258.027744 66.171172 \nL 258.386029 63.90427 \nL 258.744315 67.979884 \nL 259.1026 69.783586 \nL 259.460886 63.541856 \nL 259.819172 64.071702 \nL 260.177457 66.072615 \nL 260.535743 62.131407 \nL 260.894029 68.324545 \nL 261.252314 63.73029 \nL 261.6106 64.360657 \nL 261.968885 70.040822 \nL 262.327171 65.416418 \nL 262.685457 72.52005 \nL 263.043742 61.801781 \nL 263.402028 62.384179 \nL 263.760314 68.106777 \nL 264.118599 66.279504 \nL 264.476885 62.744547 \nL 264.83517 64.638128 \nL 265.193456 58.61498 \nL 265.551742 67.404153 \nL 265.910027 65.042645 \nL 266.268313 69.781277 \nL 266.626599 67.688415 \nL 266.984884 68.189542 \nL 267.34317 64.987175 \nL 267.701455 65.206984 \nL 268.059741 66.642019 \nL 268.418027 64.540471 \nL 268.776312 67.59684 \nL 269.134598 66.615052 \nL 269.492884 64.407701 \nL 269.851169 73.413226 \nL 270.209455 66.305761 \nL 270.56774 68.509725 \nL 270.926026 71.590525 \nL 271.284312 66.674367 \nL 271.642597 64.50662 \nL 272.000883 71.339036 \nL 272.359168 68.707958 \nL 272.717454 64.842011 \nL 273.07574 65.366187 \nL 273.434025 68.448607 \nL 273.792311 70.390233 \nL 274.150597 69.721593 \nL 274.508882 66.915465 \nL 274.867168 59.705644 \nL 275.225453 66.855878 \nL 275.583739 62.920978 \nL 275.942025 51.080245 \nL 276.30031 65.142614 \nL 276.658596 64.974923 \nL 277.016882 69.311787 \nL 277.733453 62.806994 \nL 278.450024 76.658762 \nL 278.80831 64.227214 \nL 279.166595 73.053372 \nL 279.524881 62.975212 \nL 279.883167 63.808186 \nL 280.241452 63.560192 \nL 280.599738 63.689011 \nL 280.958023 70.637514 \nL 281.316309 63.499752 \nL 281.674595 68.414123 \nL 282.391166 64.525968 \nL 282.749452 60.011311 \nL 283.107737 63.696278 \nL 283.466023 70.566681 \nL 283.824308 62.554065 \nL 284.54088 73.695084 \nL 285.257451 62.951202 \nL 285.615737 63.665021 \nL 285.974022 67.002067 \nL 286.332308 66.600706 \nL 286.690593 55.90626 \nL 287.048879 65.254833 \nL 287.407165 60.893228 \nL 287.76545 62.277201 \nL 288.123736 70.889541 \nL 288.482022 66.969039 \nL 288.840307 78.580103 \nL 289.198593 64.635178 \nL 289.556878 63.668373 \nL 289.915164 73.416248 \nL 290.27345 64.929698 \nL 290.631735 71.086747 \nL 291.348306 62.596055 \nL 291.706592 63.823241 \nL 292.064878 56.79411 \nL 292.781449 69.067972 \nL 293.139735 63.071053 \nL 293.49802 62.730962 \nL 293.856306 61.650926 \nL 294.214591 69.677733 \nL 294.572877 63.047191 \nL 294.931163 60.751031 \nL 295.289448 57.654714 \nL 295.647734 61.194694 \nL 296.00602 66.110034 \nL 296.364305 62.948411 \nL 296.722591 69.079416 \nL 297.080876 64.100752 \nL 297.439162 64.39111 \nL 297.797448 66.763292 \nL 298.155733 62.581506 \nL 298.514019 66.074325 \nL 298.872305 66.887608 \nL 299.23059 62.480378 \nL 299.588876 66.073279 \nL 299.947161 57.887173 \nL 300.305447 68.841498 \nL 300.663733 70.175435 \nL 301.022018 57.358456 \nL 301.380304 69.088544 \nL 301.73859 64.712202 \nL 302.096875 62.741099 \nL 302.455161 58.879792 \nL 302.813446 73.50311 \nL 303.171732 72.964673 \nL 303.530018 65.630113 \nL 303.888303 68.695503 \nL 304.246589 66.782094 \nL 304.604875 66.585542 \nL 304.96316 60.907622 \nL 305.321446 57.654669 \nL 305.679731 67.993845 \nL 306.038017 61.688822 \nL 306.396303 69.6595 \nL 306.754588 63.330009 \nL 307.112874 73.617375 \nL 307.829445 59.620921 \nL 308.187731 63.831405 \nL 308.546016 63.694168 \nL 308.904302 67.362405 \nL 309.262588 64.634927 \nL 309.620873 64.341638 \nL 309.979159 70.759957 \nL 310.337444 71.403612 \nL 310.69573 62.448351 \nL 311.054016 61.880091 \nL 311.412301 56.713021 \nL 311.770587 57.184845 \nL 312.128873 59.437846 \nL 312.487158 66.279609 \nL 312.845444 64.971262 \nL 313.203729 59.320952 \nL 313.562015 71.660911 \nL 313.920301 65.372486 \nL 314.278586 67.943103 \nL 314.636872 67.187816 \nL 314.995158 65.422101 \nL 315.353443 64.684924 \nL 315.711729 64.827986 \nL 316.070014 66.264428 \nL 316.4283 69.373845 \nL 316.786586 71.484336 \nL 317.144871 62.380502 \nL 317.503157 63.379337 \nL 317.861443 74.077001 \nL 318.578014 59.241723 \nL 318.936299 70.937944 \nL 319.294585 69.063883 \nL 319.652871 70.488996 \nL 320.011156 65.358603 \nL 320.369442 70.312697 \nL 320.727728 63.998936 \nL 321.086013 70.591286 \nL 321.802584 66.353653 \nL 322.16087 68.988926 \nL 322.519156 64.78313 \nL 322.877441 67.581418 \nL 323.235727 63.931203 \nL 323.594013 65.555266 \nL 323.952298 60.434196 \nL 324.310584 58.62053 \nL 324.668869 68.810742 \nL 325.385441 67.054835 \nL 325.743726 60.700827 \nL 326.102012 74.887118 \nL 326.460298 68.312457 \nL 326.818583 67.961926 \nL 327.176869 64.926698 \nL 327.535154 67.157488 \nL 327.89344 60.349654 \nL 328.251726 59.45626 \nL 328.610011 55.931744 \nL 328.968297 59.094622 \nL 329.326582 69.738586 \nL 329.684868 66.520391 \nL 330.043154 59.504319 \nL 330.401439 56.91315 \nL 330.759725 60.210435 \nL 331.118011 67.149884 \nL 331.476296 68.241171 \nL 331.834582 74.621351 \nL 332.192867 63.629032 \nL 332.551153 62.628925 \nL 332.909439 67.082527 \nL 333.267724 65.871025 \nL 333.62601 67.186715 \nL 333.984296 69.573993 \nL 334.342581 66.266903 \nL 334.700867 65.916534 \nL 335.059152 64.944943 \nL 335.417438 68.910311 \nL 335.775724 49.542431 \nL 336.134009 64.846491 \nL 336.850581 73.122086 \nL 337.208866 66.897865 \nL 337.567152 64.903741 \nL 337.925437 69.898264 \nL 338.283723 69.038893 \nL 338.642009 70.937528 \nL 339.000294 64.883601 \nL 339.35858 66.592366 \nL 339.716866 66.668782 \nL 340.075151 65.382634 \nL 340.433437 69.577519 \nL 340.791722 68.821617 \nL 341.150008 61.534207 \nL 341.508294 70.822832 \nL 341.866579 66.144306 \nL 342.224865 63.278872 \nL 342.583151 65.587582 \nL 342.941436 67.121492 \nL 343.299722 55.640135 \nL 343.658007 66.184069 \nL 344.016293 69.169446 \nL 344.374579 67.693591 \nL 344.732864 64.229865 \nL 345.09115 61.863494 \nL 345.449435 51.221182 \nL 345.807721 65.66331 \nL 346.166007 67.516427 \nL 346.524292 66.285399 \nL 346.882578 64.45204 \nL 347.240864 73.351172 \nL 347.599149 63.18252 \nL 347.957435 71.784596 \nL 348.31572 71.032038 \nL 348.674006 71.310356 \nL 349.032292 64.648347 \nL 349.390577 68.285305 \nL 349.748863 63.79556 \nL 350.465434 71.740257 \nL 350.82372 55.274526 \nL 351.182005 64.140935 \nL 351.540291 70.093632 \nL 351.898577 68.952492 \nL 352.256862 75.246659 \nL 352.615148 66.4161 \nL 352.973434 66.692128 \nL 353.331719 66.217336 \nL 353.690005 67.98381 \nL 354.04829 62.052248 \nL 354.406576 59.197497 \nL 354.764862 70.755736 \nL 355.123147 67.841923 \nL 355.481433 70.020926 \nL 355.839719 63.108393 \nL 356.198004 68.156784 \nL 356.55629 63.096202 \nL 356.914575 62.019659 \nL 357.272861 85.926931 \nL 357.631147 63.420479 \nL 357.989432 75.248944 \nL 358.347718 69.250303 \nL 358.706004 70.316566 \nL 359.064289 61.833089 \nL 359.422575 61.309547 \nL 359.78086 63.979186 \nL 360.139146 63.653989 \nL 360.497432 68.805001 \nL 360.855717 61.895015 \nL 361.572289 67.463153 \nL 361.930574 65.708286 \nL 362.28886 59.232275 \nL 362.647145 87.966807 \nL 363.005431 59.986028 \nL 363.363717 68.547522 \nL 363.722002 66.600342 \nL 364.438573 65.818641 \nL 364.796859 53.79449 \nL 365.155145 65.662269 \nL 365.51343 68.390037 \nL 365.871716 65.867707 \nL 366.230002 67.075183 \nL 366.588287 67.71149 \nL 366.946573 66.680604 \nL 367.304858 63.233267 \nL 367.663144 72.706579 \nL 368.02143 64.92412 \nL 368.379715 70.359022 \nL 368.738001 67.156177 \nL 369.096287 69.17781 \nL 369.454572 59.833061 \nL 369.812858 74.756349 \nL 370.171143 69.079003 \nL 370.529429 72.171899 \nL 370.887715 67.603621 \nL 371.246 68.870799 \nL 371.962572 72.309364 \nL 372.320857 67.78491 \nL 372.679143 67.610402 \nL 373.037428 64.768152 \nL 373.395714 70.368934 \nL 373.754 59.755716 \nL 374.470571 72.898169 \nL 374.828857 75.30287 \nL 375.187142 58.578594 \nL 375.545428 71.954394 \nL 375.903713 61.394294 \nL 376.261999 63.76604 \nL 376.620285 63.254345 \nL 376.97857 57.738432 \nL 377.336856 66.246041 \nL 377.695142 70.881861 \nL 378.411713 60.98402 \nL 378.769998 61.578387 \nL 379.128284 59.563981 \nL 379.844855 68.097875 \nL 380.203141 60.787833 \nL 380.561427 68.991524 \nL 380.919712 63.565681 \nL 381.277998 69.246839 \nL 381.636283 65.459472 \nL 381.994569 67.42506 \nL 382.352855 60.518644 \nL 382.71114 66.130527 \nL 383.069426 64.70923 \nL 383.427711 64.656056 \nL 383.785997 69.756347 \nL 384.502568 59.574469 \nL 384.860854 73.0573 \nL 385.21914 66.905059 \nL 385.577425 68.439069 \nL 385.935711 65.336921 \nL 386.293996 71.293199 \nL 386.652282 62.656114 \nL 387.010568 62.986725 \nL 387.368853 57.017274 \nL 387.727139 60.750252 \nL 388.085425 68.721346 \nL 388.44371 58.996887 \nL 388.801996 84.504111 \nL 389.160281 62.698524 \nL 389.876853 69.588414 \nL 391.309995 60.228605 \nL 391.668281 72.615682 \nL 392.026566 68.256567 \nL 392.384852 66.59448 \nL 392.743138 68.605709 \nL 393.101423 69.762539 \nL 393.459709 64.687359 \nL 393.817995 65.493845 \nL 394.17628 54.360382 \nL 394.534566 63.719175 \nL 394.892851 63.386802 \nL 395.251137 68.273519 \nL 395.609423 70.63367 \nL 395.967708 58.636305 \nL 396.325994 66.524855 \nL 396.68428 46.763858 \nL 397.042565 58.548704 \nL 397.759136 68.32713 \nL 398.117422 67.927016 \nL 398.475708 64.065675 \nL 398.833993 66.701769 \nL 399.550565 73.390922 \nL 400.267136 61.70761 \nL 400.625421 68.422565 \nL 400.983707 63.71856 \nL 401.341993 75.684631 \nL 401.700278 70.569226 \nL 402.058564 61.26562 \nL 402.416849 66.199842 \nL 402.775135 66.115168 \nL 403.133421 61.334155 \nL 403.491706 66.871388 \nL 403.849992 58.131565 \nL 404.208278 64.54967 \nL 404.566563 57.376495 \nL 404.924849 62.182917 \nL 405.283134 58.805141 \nL 405.64142 66.379931 \nL 405.999706 66.904224 \nL 406.357991 72.245971 \nL 406.716277 74.480076 \nL 407.432848 58.941911 \nL 407.791134 70.638663 \nL 408.149419 61.701286 \nL 408.507705 70.409903 \nL 408.865991 68.019672 \nL 409.224276 68.114129 \nL 409.582562 66.646389 \nL 409.940848 67.043132 \nL 410.299133 63.989412 \nL 410.657419 59.552157 \nL 411.015704 45.103225 \nL 411.37399 57.980534 \nL 411.732276 64.743347 \nL 412.090561 60.69314 \nL 412.448847 55.290772 \nL 412.807133 57.241944 \nL 413.165418 65.879326 \nL 413.523704 68.23559 \nL 413.881989 59.321841 \nL 414.240275 57.031827 \nL 414.598561 67.906361 \nL 414.956846 62.450582 \nL 415.315132 63.792158 \nL 415.673418 69.451913 \nL 416.389989 59.572544 \nL 416.748274 66.7433 \nL 417.10656 62.793335 \nL 417.464846 63.634162 \nL 417.823131 66.001845 \nL 418.181417 63.640028 \nL 418.539702 57.079641 \nL 418.897988 66.08613 \nL 419.256274 69.716806 \nL 419.614559 61.040407 \nL 419.972845 56.860429 \nL 420.331131 63.846371 \nL 420.689416 64.289057 \nL 421.047702 64.37251 \nL 421.405987 59.030207 \nL 421.764273 57.367452 \nL 422.122559 58.655697 \nL 422.480844 64.135048 \nL 423.197416 62.574647 \nL 423.555701 66.745611 \nL 423.913987 69.269473 \nL 424.272272 64.218904 \nL 424.630558 65.737739 \nL 424.988844 58.207581 \nL 425.347129 75.789066 \nL 425.705415 62.735249 \nL 426.063701 65.568396 \nL 426.421986 59.354672 \nL 426.780272 70.783655 \nL 427.138557 65.575072 \nL 427.496843 68.422403 \nL 427.855129 54.513984 \nL 428.213414 64.419166 \nL 428.5717 69.67227 \nL 428.929986 71.488023 \nL 429.288271 63.900839 \nL 430.004842 68.81474 \nL 430.363128 62.713347 \nL 430.721414 68.697045 \nL 431.079699 65.019238 \nL 431.437985 67.007997 \nL 431.796271 61.171445 \nL 432.154556 63.575623 \nL 432.512842 57.339965 \nL 432.871127 65.307184 \nL 433.229413 57.639627 \nL 433.587699 69.606326 \nL 433.945984 64.692267 \nL 434.30427 66.160895 \nL 434.662556 66.148746 \nL 435.020841 61.064251 \nL 435.379127 65.224742 \nL 435.737412 67.075501 \nL 436.095698 67.010397 \nL 436.453984 59.779636 \nL 436.812269 63.777176 \nL 437.170555 59.613413 \nL 437.52884 71.977635 \nL 437.887126 59.348002 \nL 438.603697 80.529205 \nL 438.961983 57.09829 \nL 439.320269 55.143933 \nL 439.678554 66.179696 \nL 440.03684 60.51093 \nL 440.395125 67.922266 \nL 440.753411 68.015211 \nL 441.111697 57.769767 \nL 441.469982 56.245479 \nL 441.828268 64.107829 \nL 442.186554 65.288127 \nL 442.544839 68.542874 \nL 442.903125 66.519742 \nL 443.26141 66.751901 \nL 443.619696 71.971887 \nL 443.977982 66.335348 \nL 444.336267 66.474694 \nL 444.694553 68.37803 \nL 445.052839 67.588899 \nL 445.411124 58.767951 \nL 445.76941 64.202213 \nL 446.127695 62.090221 \nL 446.485981 68.130305 \nL 446.844267 61.091786 \nL 447.202552 61.614833 \nL 447.560838 63.580841 \nL 447.919124 68.968846 \nL 448.277409 55.736381 \nL 448.99398 65.181529 \nL 449.352266 64.582669 \nL 449.710552 68.535325 \nL 450.068837 63.87824 \nL 450.427123 69.792794 \nL 450.785409 61.043123 \nL 451.143694 58.161107 \nL 451.50198 60.842912 \nL 451.860265 64.501253 \nL 452.218551 65.520005 \nL 452.576837 64.799188 \nL 453.293408 66.41465 \nL 453.651694 65.582398 \nL 454.009979 63.885625 \nL 454.368265 65.072049 \nL 454.72655 71.136242 \nL 455.084836 63.152391 \nL 455.443122 63.31852 \nL 455.801407 58.511469 \nL 456.517978 67.525435 \nL 456.876264 70.930711 \nL 457.23455 64.344759 \nL 457.592835 66.299195 \nL 457.951121 59.912394 \nL 458.309407 67.649103 \nL 458.667692 66.253321 \nL 459.025978 62.443645 \nL 459.384263 63.714579 \nL 459.742549 67.000476 \nL 460.45912 56.816236 \nL 461.175692 59.780685 \nL 461.533977 65.172085 \nL 461.892263 64.691525 \nL 462.250548 71.03555 \nL 462.608834 61.667814 \nL 462.96712 62.786047 \nL 463.325405 66.816252 \nL 463.683691 64.244852 \nL 464.041977 66.293676 \nL 464.400262 60.51789 \nL 464.758548 69.127774 \nL 465.116833 68.407182 \nL 465.475119 66.694821 \nL 465.833405 64.078427 \nL 466.19169 60.153681 \nL 466.549976 68.169014 \nL 466.908262 62.472917 \nL 467.266547 61.719277 \nL 467.624833 64.320961 \nL 467.983118 67.998588 \nL 468.69969 62.684149 \nL 469.057975 59.163912 \nL 469.416261 59.253979 \nL 469.774547 62.078538 \nL 470.132832 63.398584 \nL 470.491118 60.099072 \nL 470.849403 70.630342 \nL 471.207689 63.639305 \nL 471.565975 68.234563 \nL 471.92426 66.509367 \nL 472.282546 62.262066 \nL 472.640832 63.348785 \nL 472.999117 60.415694 \nL 473.357403 53.749733 \nL 473.715688 67.091166 \nL 474.073974 67.24883 \nL 474.43226 59.033028 \nL 474.790545 60.409211 \nL 475.148831 58.261554 \nL 475.507116 62.993443 \nL 475.865402 64.479914 \nL 476.223688 63.660955 \nL 476.581973 79.498984 \nL 476.940259 67.771467 \nL 477.298545 67.789244 \nL 477.65683 58.967655 \nL 478.015116 64.82469 \nL 478.373401 66.472933 \nL 478.731687 66.490285 \nL 479.089973 57.575773 \nL 479.448258 61.406819 \nL 479.806544 67.374701 \nL 480.16483 67.316429 \nL 480.523115 68.339953 \nL 480.881401 61.282623 \nL 481.239686 64.857497 \nL 481.597972 66.060063 \nL 481.956258 76.768085 \nL 482.314543 67.721824 \nL 482.672829 61.61029 \nL 483.031115 66.965709 \nL 483.3894 65.49271 \nL 483.747686 65.98533 \nL 484.105971 67.086662 \nL 484.464257 67.28698 \nL 484.822543 63.36315 \nL 485.180828 62.983274 \nL 485.539114 66.504702 \nL 486.255685 61.73613 \nL 486.613971 67.831522 \nL 486.972256 61.905683 \nL 487.330542 70.295413 \nL 487.688828 65.278216 \nL 488.047113 68.511077 \nL 488.405399 64.078377 \nL 488.763685 65.668986 \nL 489.12197 64.850822 \nL 489.480256 72.136138 \nL 489.838541 69.041498 \nL 490.196827 64.863534 \nL 490.555113 66.67277 \nL 490.913398 69.125338 \nL 491.271684 64.049073 \nL 491.62997 66.452773 \nL 491.988255 66.930654 \nL 492.346541 64.126972 \nL 492.704826 66.834911 \nL 493.063112 72.70271 \nL 493.421398 67.833704 \nL 493.779683 71.554083 \nL 494.137969 62.044303 \nL 494.496254 60.171601 \nL 494.85454 63.191032 \nL 495.212826 63.294455 \nL 495.571111 64.679781 \nL 495.929397 54.971092 \nL 496.287683 60.597765 \nL 496.645968 60.592722 \nL 497.004254 69.419393 \nL 497.362539 56.847767 \nL 497.720825 64.222707 \nL 498.079111 57.003165 \nL 498.437396 62.759649 \nL 498.795682 65.183501 \nL 499.153968 51.828146 \nL 499.512253 61.900712 \nL 499.870539 50.045039 \nL 500.228824 62.365664 \nL 500.58711 66.102463 \nL 500.945396 68.186814 \nL 501.303681 56.672288 \nL 501.661967 66.875975 \nL 502.020253 61.697084 \nL 502.378538 59.280046 \nL 502.736824 53.417759 \nL 503.095109 63.320707 \nL 503.453395 66.622443 \nL 503.811681 62.339609 \nL 504.528252 60.715201 \nL 504.886538 77.078092 \nL 505.244823 61.142993 \nL 505.603109 67.450362 \nL 505.961394 49.578539 \nL 506.31968 58.064476 \nL 506.677966 59.996535 \nL 507.036251 58.354495 \nL 507.394537 61.657647 \nL 507.752823 66.138281 \nL 508.111108 56.589425 \nL 508.469394 59.055435 \nL 508.827679 57.416558 \nL 509.185965 65.497237 \nL 509.544251 54.763254 \nL 509.902536 65.562224 \nL 510.260822 61.531668 \nL 510.619107 66.680242 \nL 510.977393 68.484011 \nL 511.335679 62.851732 \nL 511.693964 71.6326 \nL 512.05225 62.068545 \nL 512.410536 72.638026 \nL 513.127107 57.969696 \nL 513.485392 57.966566 \nL 514.201964 65.549228 \nL 514.560249 64.938528 \nL 514.918535 63.348164 \nL 515.276821 67.278854 \nL 515.635106 66.989731 \nL 515.993392 57.973375 \nL 516.351677 69.834826 \nL 516.709963 67.149313 \nL 517.426534 59.964466 \nL 517.78482 63.13754 \nL 518.143106 62.243444 \nL 518.501391 65.874413 \nL 518.859677 53.481337 \nL 519.217962 60.161737 \nL 519.576248 60.344304 \nL 519.934534 57.957565 \nL 520.292819 57.024938 \nL 520.651105 64.64148 \nL 521.009391 65.667202 \nL 521.367676 70.244192 \nL 521.725962 65.946148 \nL 522.084247 68.753641 \nL 522.800819 56.54611 \nL 523.159104 59.786531 \nL 523.51739 67.535757 \nL 524.592247 66.954112 \nL 524.950532 67.458506 \nL 525.308818 61.346069 \nL 525.667104 57.56422 \nL 526.025389 55.63329 \nL 526.383675 60.48081 \nL 526.741961 61.089684 \nL 527.100246 67.13451 \nL 527.458532 68.781823 \nL 527.816817 64.764338 \nL 528.175103 65.169516 \nL 528.533389 67.696888 \nL 528.891674 65.819024 \nL 529.24996 69.112143 \nL 529.608245 66.35414 \nL 529.966531 59.685714 \nL 530.324817 57.051798 \nL 530.683102 50.603135 \nL 531.041388 65.418295 \nL 531.399674 68.137548 \nL 532.116245 58.856955 \nL 532.47453 67.130971 \nL 532.832816 62.829706 \nL 533.191102 65.87411 \nL 533.549387 61.470011 \nL 533.907673 68.002264 \nL 534.265959 67.004732 \nL 534.624244 61.611792 \nL 534.98253 62.344187 \nL 535.699101 64.369751 \nL 536.057387 62.129788 \nL 536.415672 66.250999 \nL 536.773958 64.413371 \nL 537.132244 59.858311 \nL 537.490529 64.796956 \nL 537.848815 62.192648 \nL 538.2071 66.215619 \nL 538.565386 67.372982 \nL 538.923672 59.09858 \nL 539.281957 64.533664 \nL 539.640243 63.248998 \nL 539.998529 58.916747 \nL 540.356814 70.994115 \nL 540.7151 65.243335 \nL 541.073385 65.031086 \nL 541.431671 57.87335 \nL 541.789957 71.007744 \nL 542.148242 63.896786 \nL 542.506528 65.802335 \nL 542.864814 60.482453 \nL 543.223099 56.931374 \nL 543.581385 63.802428 \nL 543.93967 57.607708 \nL 544.297956 53.458038 \nL 544.656242 59.865874 \nL 545.014527 56.869614 \nL 545.731099 70.238413 \nL 546.089384 59.750217 \nL 546.44767 64.402106 \nL 546.805955 66.088542 \nL 547.164241 64.765557 \nL 547.522527 57.38575 \nL 547.880812 64.34838 \nL 548.239098 67.755771 \nL 548.597383 65.284375 \nL 549.313955 53.549791 \nL 549.67224 66.605949 \nL 550.030526 71.137074 \nL 550.388812 65.066491 \nL 550.747097 61.016001 \nL 551.105383 61.806441 \nL 551.463668 68.301645 \nL 551.821954 68.660001 \nL 552.18024 66.111152 \nL 552.538525 66.472367 \nL 552.896811 59.418836 \nL 553.255097 59.745692 \nL 553.971668 64.801605 \nL 554.329953 65.504177 \nL 554.688239 70.951196 \nL 555.046525 55.738786 \nL 555.40481 64.219091 \nL 555.763096 64.996426 \nL 556.121382 60.862161 \nL 556.479667 55.037043 \nL 556.837953 64.827442 \nL 557.196238 68.578489 \nL 557.554524 63.330909 \nL 557.91281 68.425881 \nL 558.271095 69.615399 \nL 558.987667 59.932074 \nL 559.345952 60.379009 \nL 559.704238 64.367917 \nL 560.062523 59.552199 \nL 560.420809 62.711155 \nL 560.779095 55.976186 \nL 561.13738 59.432094 \nL 561.495666 60.294712 \nL 561.853952 73.252197 \nL 562.570523 60.713748 \nL 562.928808 54.308811 \nL 563.287094 67.368984 \nL 563.64538 69.403688 \nL 564.003665 64.114615 \nL 564.361951 61.825068 \nL 564.720237 60.803383 \nL 565.078522 57.305976 \nL 565.436808 58.144581 \nL 565.795093 62.130459 \nL 566.153379 61.544062 \nL 566.511665 65.81367 \nL 567.228236 56.425812 \nL 567.586521 61.887927 \nL 567.944807 58.9493 \nL 568.303093 62.456932 \nL 568.661378 54.330529 \nL 569.019664 60.15521 \nL 569.37795 55.000783 \nL 569.736235 62.184161 \nL 570.094521 51.803631 \nL 570.452806 58.994066 \nL 570.811092 56.524934 \nL 571.169378 74.710647 \nL 571.527663 55.593744 \nL 571.885949 62.103927 \nL 572.244235 60.524711 \nL 572.60252 63.323362 \nL 572.960806 63.074581 \nL 573.319091 64.302091 \nL 573.677377 62.546048 \nL 574.035663 55.308192 \nL 574.393948 74.615128 \nL 574.752234 63.907475 \nL 575.11052 65.834481 \nL 575.468805 65.807827 \nL 575.827091 62.044758 \nL 576.543662 70.969802 \nL 576.901948 66.965025 \nL 577.260233 65.47815 \nL 577.618519 66.399224 \nL 577.976805 60.232977 \nL 578.33509 68.419138 \nL 578.693376 66.222159 \nL 579.409947 59.42342 \nL 580.126518 64.527782 \nL 580.484804 51.709806 \nL 580.84309 65.928818 \nL 581.201375 56.395364 \nL 581.559661 69.608647 \nL 581.917946 74.180889 \nL 582.276232 63.53949 \nL 582.634518 56.984787 \nL 582.992803 56.338698 \nL 583.351089 65.473576 \nL 583.709374 63.435802 \nL 584.06766 63.284034 \nL 584.425946 64.204542 \nL 584.784231 64.811995 \nL 585.142517 69.877701 \nL 585.500803 65.233279 \nL 585.859088 66.213528 \nL 586.217374 63.795899 \nL 586.575659 62.95624 \nL 586.933945 46.341619 \nL 587.650516 61.329996 \nL 588.008802 63.113105 \nL 588.367088 66.088277 \nL 588.725373 62.707533 \nL 589.083659 65.712947 \nL 589.441944 61.441358 \nL 589.80023 65.736968 \nL 590.158516 66.409229 \nL 590.516801 60.653505 \nL 590.875087 61.909963 \nL 591.233373 70.940835 \nL 591.591658 59.293811 \nL 591.949944 77.688465 \nL 592.308229 67.297909 \nL 592.666515 65.745168 \nL 593.024801 63.097275 \nL 593.383086 54.13325 \nL 594.099658 65.658218 \nL 594.457943 61.546811 \nL 594.816229 64.923893 \nL 595.174514 65.799636 \nL 595.5328 59.358258 \nL 595.891086 69.94 \nL 596.249371 70.876108 \nL 596.965943 64.45377 \nL 597.324228 67.433055 \nL 597.682514 66.398493 \nL 598.040799 59.585784 \nL 598.399085 64.825538 \nL 598.757371 62.226179 \nL 599.115656 64.264434 \nL 599.473942 57.313593 \nL 599.832228 59.545714 \nL 600.190513 60.188012 \nL 600.548799 68.559709 \nL 600.907084 68.109094 \nL 601.26537 58.985112 \nL 601.623656 67.162742 \nL 601.981941 58.706383 \nL 602.340227 61.426057 \nL 602.698512 62.831612 \nL 603.056798 66.547779 \nL 603.415084 64.405532 \nL 603.773369 63.808253 \nL 604.131655 61.673967 \nL 604.489941 68.080293 \nL 604.848226 62.76245 \nL 605.206512 61.036443 \nL 605.564797 69.40894 \nL 605.923083 62.609099 \nL 606.281369 58.984986 \nL 606.639654 70.97912 \nL 606.99794 59.559741 \nL 607.356226 61.716944 \nL 607.714511 60.135317 \nL 608.072797 51.486148 \nL 608.431082 69.912045 \nL 608.789368 60.915579 \nL 609.147654 69.628034 \nL 609.505939 72.662737 \nL 609.864225 62.784956 \nL 610.222511 65.465518 \nL 610.580796 63.034298 \nL 610.939082 56.566616 \nL 611.297367 59.209518 \nL 611.655653 69.171486 \nL 612.372224 52.538684 \nL 612.73051 61.958357 \nL 613.088796 59.134486 \nL 613.447081 68.009775 \nL 613.805367 50.058977 \nL 614.163652 65.595535 \nL 614.521938 65.583668 \nL 615.238509 74.375933 \nL 615.596795 68.725648 \nL 615.955081 65.47104 \nL 616.313366 69.674884 \nL 616.671652 66.00469 \nL 617.029937 64.587421 \nL 617.388223 64.9596 \nL 617.746509 61.687252 \nL 618.104794 57.081027 \nL 618.46308 60.419963 \nL 619.179651 61.51458 \nL 619.537937 50.735423 \nL 619.896222 58.60088 \nL 620.254508 63.599517 \nL 620.612794 61.030657 \nL 620.971079 64.867666 \nL 621.329365 66.939593 \nL 621.68765 70.810633 \nL 622.045936 55.975342 \nL 622.404222 57.823684 \nL 622.762507 69.532085 \nL 623.120793 60.148982 \nL 623.479079 67.993431 \nL 623.837364 57.329478 \nL 624.19565 60.380984 \nL 624.553935 61.334322 \nL 624.912221 65.548769 \nL 625.270507 61.408082 \nL 625.628792 60.476854 \nL 626.345364 65.17116 \nL 626.703649 60.167964 \nL 627.061935 57.885133 \nL 627.42022 73.952208 \nL 627.778506 76.343459 \nL 628.136792 69.796349 \nL 628.495077 66.05606 \nL 628.853363 61.057037 \nL 629.211649 64.921127 \nL 629.569934 63.060292 \nL 629.92822 64.56793 \nL 631.003077 51.417911 \nL 631.361362 59.821422 \nL 631.719648 57.897667 \nL 632.077934 66.140119 \nL 632.436219 66.16982 \nL 632.794505 69.885737 \nL 633.511076 64.733136 \nL 633.869362 63.856855 \nL 634.227647 70.089836 \nL 634.585933 60.226587 \nL 634.944219 57.188078 \nL 635.302504 61.816048 \nL 635.66079 55.825029 \nL 636.019075 64.538988 \nL 636.377361 59.179792 \nL 636.735647 60.920373 \nL 637.093932 64.826101 \nL 637.452218 58.617035 \nL 637.810504 69.062441 \nL 638.168789 71.45653 \nL 638.527075 58.951671 \nL 638.88536 64.840411 \nL 639.243646 65.625218 \nL 639.601932 70.870164 \nL 639.960217 65.526708 \nL 640.318503 53.983416 \nL 640.676788 63.572207 \nL 641.035074 60.46087 \nL 641.39336 58.38096 \nL 641.751645 64.457861 \nL 642.109931 55.627564 \nL 642.826502 66.39016 \nL 643.543073 63.179511 \nL 643.901359 66.078072 \nL 644.259645 63.877707 \nL 644.61793 66.542429 \nL 644.976216 65.644242 \nL 645.334502 67.098941 \nL 645.692787 67.756155 \nL 646.051073 58.633382 \nL 646.409358 63.654372 \nL 646.767644 65.675936 \nL 647.12593 65.914124 \nL 647.484215 59.579843 \nL 647.842501 59.720312 \nL 648.200787 60.3944 \nL 648.559072 66.038539 \nL 648.917358 54.019283 \nL 649.275643 63.516279 \nL 649.633929 64.564861 \nL 649.992215 67.51888 \nL 650.3505 62.344196 \nL 650.708786 63.091951 \nL 651.067072 58.644377 \nL 651.425357 59.431519 \nL 651.783643 57.602376 \nL 652.141928 61.586317 \nL 652.500214 42.601207 \nL 652.8585 57.047848 \nL 653.216785 62.865811 \nL 653.575071 59.892575 \nL 653.933357 63.750206 \nL 654.291642 61.825862 \nL 654.649928 66.16523 \nL 655.008213 66.679426 \nL 655.366499 57.229103 \nL 655.724785 60.241272 \nL 656.08307 60.094372 \nL 656.441356 60.36278 \nL 656.799642 55.641388 \nL 657.157927 64.197058 \nL 657.516213 62.841784 \nL 657.874498 53.45253 \nL 658.232784 56.694297 \nL 658.59107 63.317946 \nL 658.949355 67.158398 \nL 659.307641 68.933919 \nL 659.665926 68.826983 \nL 660.024212 59.059969 \nL 660.382498 65.394733 \nL 660.740783 62.18727 \nL 661.099069 63.442092 \nL 661.457355 69.562066 \nL 661.81564 63.633069 \nL 662.173926 64.745741 \nL 662.532211 52.560325 \nL 662.890497 67.652319 \nL 663.248783 62.907193 \nL 663.965354 70.337247 \nL 664.681925 60.004721 \nL 665.040211 75.086104 \nL 665.398496 64.297942 \nL 665.756782 65.331531 \nL 666.115068 65.91773 \nL 666.473353 63.520572 \nL 666.831639 58.119949 \nL 667.189925 61.510854 \nL 667.54821 63.075717 \nL 667.906496 61.567894 \nL 668.264781 66.335554 \nL 668.623067 65.288291 \nL 668.981353 61.119941 \nL 669.339638 68.1018 \nL 669.697924 67.566772 \nL 670.05621 62.137881 \nL 670.414495 63.036394 \nL 670.772781 58.620421 \nL 671.131066 61.613175 \nL 671.489352 63.455363 \nL 672.205923 52.660831 \nL 672.564209 56.201991 \nL 673.28078 66.9075 \nL 673.639066 59.832733 \nL 673.997351 61.776712 \nL 674.355637 67.40996 \nL 674.713923 56.994212 \nL 675.072208 62.247943 \nL 675.430494 57.977817 \nL 675.788779 57.785055 \nL 676.147065 49.162592 \nL 676.863636 64.00183 \nL 676.863636 64.00183 \n\" style=\"fill:none;stroke:#1f77b4;stroke-linecap:square;stroke-width:1.5;\"/>\n   </g>\n   <g id=\"line2d_80\">\n    <path clip-path=\"url(#p3aff99f2fc)\" d=\"M 68.136364 56.508552 \nL 68.494649 63.955352 \nL 68.852935 77.724267 \nL 69.569506 121.767533 \nL 70.286077 165.791918 \nL 70.644363 180.83532 \nL 71.002649 186.306772 \nL 71.360934 203.553295 \nL 71.71922 208.291816 \nL 72.077505 219.212512 \nL 72.435791 199.466888 \nL 72.794077 216.147113 \nL 73.152362 212.973354 \nL 73.510648 220.42428 \nL 73.868934 216.485075 \nL 74.227219 209.647278 \nL 74.585505 197.636393 \nL 74.94379 219.555176 \nL 75.302076 221.053453 \nL 75.660362 191.846791 \nL 76.018647 218.540875 \nL 76.376933 221.317992 \nL 77.093504 175.075345 \nL 77.45179 204.581443 \nL 77.810075 171.860969 \nL 78.168361 191.352196 \nL 78.526647 233.367916 \nL 78.884932 231.359004 \nL 79.243218 233.198276 \nL 79.959789 266.645455 \nL 80.318075 239.734851 \nL 80.67636 229.106363 \nL 81.034646 212.567916 \nL 81.392932 226.636524 \nL 82.109503 205.764887 \nL 82.467789 184.91586 \nL 83.18436 225.609308 \nL 83.542645 173.623623 \nL 83.900931 155.501957 \nL 84.259217 158.055533 \nL 84.617502 174.110725 \nL 84.975788 212.903319 \nL 85.692359 177.885964 \nL 86.050645 211.148117 \nL 86.40893 210.713001 \nL 86.767216 188.103186 \nL 87.483787 180.221831 \nL 87.842073 82.503114 \nL 88.200358 137.556292 \nL 88.558644 171.915008 \nL 88.91693 171.854478 \nL 89.275215 164.29773 \nL 89.633501 168.481792 \nL 89.991787 160.829064 \nL 90.350072 162.765267 \nL 90.708358 179.723415 \nL 91.066643 152.260576 \nL 91.424929 137.004461 \nL 91.783215 149.285395 \nL 92.1415 138.936378 \nL 92.858072 156.118467 \nL 93.216357 140.558704 \nL 93.574643 132.562633 \nL 93.932928 118.968409 \nL 94.291214 75.094652 \nL 94.6495 93.970422 \nL 95.007785 101.686109 \nL 95.366071 127.040692 \nL 95.724357 125.530946 \nL 96.082642 125.856914 \nL 96.440928 128.806217 \nL 96.799213 127.877709 \nL 97.157499 130.18338 \nL 97.515785 119.913822 \nL 97.87407 133.689414 \nL 98.590642 110.576686 \nL 98.948927 127.771288 \nL 99.307213 134.351891 \nL 99.665498 121.84298 \nL 100.023784 115.044968 \nL 100.38207 134.833864 \nL 100.740355 118.313433 \nL 101.098641 118.955063 \nL 101.456927 122.13864 \nL 101.815212 118.151588 \nL 102.173498 87.277757 \nL 102.890069 121.462267 \nL 103.248355 115.462718 \nL 103.60664 102.116172 \nL 103.964926 132.251494 \nL 104.323212 115.87952 \nL 104.681497 125.163167 \nL 105.039783 124.590913 \nL 105.398068 120.039157 \nL 105.756354 133.54976 \nL 106.11464 116.884901 \nL 106.472925 111.189061 \nL 106.831211 112.503519 \nL 107.189496 109.736258 \nL 107.547782 119.709328 \nL 107.906068 115.502799 \nL 108.622639 138.684168 \nL 108.980925 113.765244 \nL 110.055781 129.203896 \nL 110.414067 131.258165 \nL 110.772353 124.55854 \nL 111.130638 114.335011 \nL 111.488924 87.645607 \nL 111.84721 98.957265 \nL 112.205495 114.605636 \nL 112.922066 123.2528 \nL 113.280352 117.633351 \nL 113.638638 122.416827 \nL 113.996923 132.293353 \nL 114.355209 123.881471 \nL 114.713495 128.015408 \nL 115.07178 134.074263 \nL 115.430066 126.455228 \nL 115.788351 128.950863 \nL 116.146637 126.386149 \nL 116.504923 116.031484 \nL 117.221494 136.961514 \nL 117.57978 130.499545 \nL 117.938065 130.669205 \nL 118.296351 127.719225 \nL 118.654636 122.204523 \nL 119.012922 104.576741 \nL 119.729493 128.610396 \nL 120.087779 124.04208 \nL 120.446065 127.924251 \nL 120.80435 122.765401 \nL 121.520921 117.005513 \nL 121.879207 124.005293 \nL 122.237493 124.974766 \nL 122.595778 131.945548 \nL 123.31235 113.446723 \nL 123.670635 119.136273 \nL 124.028921 118.130469 \nL 124.387206 117.736973 \nL 124.745492 121.298227 \nL 125.103778 116.520255 \nL 125.462063 119.9161 \nL 125.820349 129.654275 \nL 126.178634 117.433154 \nL 126.53692 125.655058 \nL 126.895206 122.953376 \nL 127.253491 123.908497 \nL 127.611777 111.211188 \nL 127.970063 116.533993 \nL 128.328348 97.362763 \nL 128.686634 109.220453 \nL 129.044919 124.862714 \nL 129.403205 114.63316 \nL 129.761491 124.316904 \nL 130.119776 98.978857 \nL 130.478062 113.861746 \nL 130.836348 113.423595 \nL 131.194633 122.755782 \nL 131.552919 101.186073 \nL 131.911204 124.386802 \nL 132.26949 122.934135 \nL 132.627776 117.682911 \nL 132.986061 118.391555 \nL 133.344347 111.896242 \nL 133.702633 113.112646 \nL 134.060918 115.778833 \nL 134.419204 115.669128 \nL 134.777489 116.814152 \nL 135.494061 123.45903 \nL 135.852346 122.741889 \nL 136.210632 111.266761 \nL 136.568918 123.198658 \nL 136.927203 108.136395 \nL 137.285489 120.079031 \nL 137.643774 118.791974 \nL 138.00206 112.150179 \nL 138.360346 118.372322 \nL 138.718631 116.874898 \nL 139.076917 117.042637 \nL 139.435203 118.707112 \nL 139.793488 119.102738 \nL 140.151774 122.008346 \nL 140.510059 126.349232 \nL 140.868345 126.045519 \nL 141.226631 123.558583 \nL 141.584916 115.943901 \nL 141.943202 126.984975 \nL 142.301488 115.603249 \nL 142.659773 93.549473 \nL 143.018059 92.861085 \nL 143.376344 95.073927 \nL 143.73463 129.337242 \nL 144.092916 126.415569 \nL 144.451201 125.812131 \nL 144.809487 135.533945 \nL 145.167772 120.558666 \nL 145.526058 117.28642 \nL 145.884344 119.066172 \nL 146.242629 110.000118 \nL 146.959201 120.788116 \nL 147.317486 120.160098 \nL 147.675772 109.267886 \nL 148.034057 112.457233 \nL 148.392343 119.967222 \nL 148.750629 114.03443 \nL 149.108914 116.715851 \nL 149.4672 116.227563 \nL 149.825486 103.111025 \nL 150.183771 107.984985 \nL 151.258628 127.004799 \nL 151.616914 125.221273 \nL 151.975199 114.684442 \nL 152.333485 111.031499 \nL 152.691771 115.394723 \nL 153.050056 126.240348 \nL 153.408342 86.606436 \nL 153.766627 101.410047 \nL 154.124913 120.865939 \nL 154.483199 117.483193 \nL 154.841484 111.752507 \nL 155.19977 115.963561 \nL 155.558056 103.616345 \nL 155.916341 120.764393 \nL 156.274627 111.249248 \nL 156.991198 114.12376 \nL 157.349484 76.954141 \nL 157.707769 62.324575 \nL 158.066055 90.939846 \nL 158.424341 109.761016 \nL 158.782626 104.489233 \nL 159.140912 112.462189 \nL 159.499197 109.966112 \nL 159.857483 108.797971 \nL 160.215769 109.562266 \nL 160.574054 112.343218 \nL 160.93234 110.911948 \nL 161.290626 115.0725 \nL 161.648911 107.159221 \nL 162.007197 110.095065 \nL 162.365482 111.052245 \nL 162.723768 111.610611 \nL 163.082054 109.817324 \nL 163.440339 111.642121 \nL 164.15691 106.204102 \nL 164.515196 106.200963 \nL 164.873482 107.56087 \nL 165.231767 110.302483 \nL 165.590053 102.675179 \nL 165.948339 101.102678 \nL 166.66491 112.270452 \nL 167.023195 109.406834 \nL 167.381481 111.436906 \nL 167.739767 103.354585 \nL 168.098052 102.350287 \nL 168.456338 108.452036 \nL 168.814624 106.648204 \nL 169.172909 106.939284 \nL 169.88948 47.444558 \nL 170.247766 99.889743 \nL 170.606052 95.826274 \nL 170.964337 102.271939 \nL 171.322623 101.3593 \nL 171.680909 103.13196 \nL 172.039194 103.178898 \nL 172.39748 98.210774 \nL 172.755765 101.604056 \nL 173.114051 117.596943 \nL 173.472337 116.547127 \nL 174.188908 102.969514 \nL 174.547194 109.658767 \nL 174.905479 107.960177 \nL 175.263765 98.896266 \nL 175.62205 102.546268 \nL 175.980336 102.035554 \nL 176.338622 106.80735 \nL 177.055193 103.436428 \nL 177.413479 103.084147 \nL 177.771764 104.965196 \nL 178.13005 100.040881 \nL 178.488335 105.526367 \nL 178.846621 106.882647 \nL 179.204907 106.600585 \nL 179.563192 99.142562 \nL 179.921478 107.079887 \nL 180.279763 95.017363 \nL 180.638049 95.124283 \nL 180.996335 89.082426 \nL 181.35462 93.491228 \nL 181.712906 96.439814 \nL 182.071192 89.397442 \nL 182.429477 99.295474 \nL 182.787763 95.686899 \nL 183.146048 104.999614 \nL 183.504334 101.377262 \nL 183.86262 101.464131 \nL 184.220905 102.238517 \nL 184.579191 97.663697 \nL 184.937477 94.779344 \nL 185.295762 95.907865 \nL 185.654048 96.660062 \nL 186.012333 99.259487 \nL 186.370619 87.019538 \nL 186.728905 92.899782 \nL 187.445476 100.798337 \nL 187.803762 94.050697 \nL 188.162047 95.69125 \nL 188.520333 103.910714 \nL 188.878618 82.982623 \nL 189.236904 83.841286 \nL 189.59519 95.596037 \nL 189.953475 92.852468 \nL 190.311761 96.135364 \nL 190.670047 94.417484 \nL 191.028332 86.805352 \nL 191.386618 96.535902 \nL 191.744903 87.926495 \nL 192.103189 94.690397 \nL 192.461475 92.860756 \nL 192.81976 95.507258 \nL 193.178046 83.113606 \nL 193.894617 94.567006 \nL 194.252903 96.548283 \nL 194.611188 88.278096 \nL 194.969474 44.646933 \nL 195.686045 73.244848 \nL 196.044331 80.515912 \nL 196.402617 81.817527 \nL 196.760902 82.321486 \nL 197.119188 87.117272 \nL 197.477473 86.095148 \nL 197.835759 86.814797 \nL 198.194045 90.405095 \nL 198.55233 89.82306 \nL 198.910616 88.541509 \nL 199.268901 90.688832 \nL 199.627187 97.282204 \nL 199.985473 94.694593 \nL 200.343758 87.762812 \nL 200.702044 91.977492 \nL 201.06033 85.958472 \nL 201.418615 89.049363 \nL 201.776901 90.305221 \nL 202.135186 88.564442 \nL 202.493472 89.038043 \nL 203.210043 92.159404 \nL 203.568329 92.324808 \nL 203.926615 91.925626 \nL 204.2849 77.084323 \nL 204.643186 91.084291 \nL 205.001471 91.1943 \nL 205.359757 93.406768 \nL 205.718043 91.508914 \nL 206.076328 88.510164 \nL 206.434614 78.996585 \nL 206.7929 88.897751 \nL 207.151185 93.234106 \nL 207.509471 87.802559 \nL 207.867756 93.830709 \nL 208.226042 85.773489 \nL 208.942613 91.597877 \nL 209.300899 90.479602 \nL 209.659185 91.409075 \nL 210.01747 94.777684 \nL 210.375756 87.189784 \nL 210.734041 92.252408 \nL 211.092327 92.610182 \nL 211.450613 86.970121 \nL 211.808898 90.847136 \nL 212.167184 87.385094 \nL 212.52547 85.003826 \nL 212.883755 66.485219 \nL 213.242041 83.226582 \nL 213.600326 88.582832 \nL 213.958612 90.534756 \nL 214.316898 87.056612 \nL 215.033469 89.611818 \nL 215.391755 86.800675 \nL 215.75004 91.412379 \nL 216.108326 86.69665 \nL 216.466611 92.69856 \nL 216.824897 86.888194 \nL 217.183183 84.151747 \nL 217.541468 91.59053 \nL 217.899754 87.445735 \nL 218.258039 88.035182 \nL 218.616325 88.201052 \nL 218.974611 89.06085 \nL 219.332896 94.651277 \nL 219.691182 83.228395 \nL 220.049468 88.767888 \nL 220.766039 86.576244 \nL 221.124324 88.547478 \nL 221.48261 89.716598 \nL 221.840896 93.138442 \nL 222.557467 81.442926 \nL 222.915753 90.199087 \nL 223.274038 84.387787 \nL 223.632324 88.983723 \nL 223.990609 90.107429 \nL 224.348895 86.890659 \nL 224.707181 89.18771 \nL 225.065466 88.2719 \nL 225.423752 91.373502 \nL 225.782038 90.805409 \nL 226.140323 90.688809 \nL 226.498609 88.038432 \nL 226.856894 90.376388 \nL 227.21518 95.286649 \nL 227.573466 82.347735 \nL 227.931751 83.990966 \nL 228.290037 92.244966 \nL 228.648323 91.476247 \nL 229.006608 91.574148 \nL 229.364894 90.979708 \nL 229.723179 87.598886 \nL 230.081465 94.734248 \nL 230.439751 43.304652 \nL 230.798036 56.967069 \nL 231.156322 85.955901 \nL 231.514608 87.42326 \nL 231.872893 85.465177 \nL 232.231179 91.131776 \nL 232.589464 85.871901 \nL 233.306036 89.142343 \nL 233.664321 91.922693 \nL 234.022607 96.634884 \nL 234.380893 92.38448 \nL 234.739178 90.556572 \nL 235.097464 87.34234 \nL 235.455749 89.656752 \nL 235.814035 89.153709 \nL 236.172321 91.936187 \nL 236.530606 84.645396 \nL 236.888892 90.84807 \nL 237.247177 87.995897 \nL 237.605463 87.939688 \nL 237.963749 86.935418 \nL 238.322034 95.647517 \nL 238.68032 90.177179 \nL 239.038606 87.996234 \nL 239.396891 92.646298 \nL 239.755177 93.821749 \nL 240.113462 81.477119 \nL 240.471748 87.354717 \nL 240.830034 88.377067 \nL 241.188319 91.168659 \nL 241.546605 87.940302 \nL 241.904891 91.659998 \nL 242.263176 86.387851 \nL 242.621462 91.429356 \nL 242.979747 90.423056 \nL 243.338033 86.474955 \nL 244.054604 90.929616 \nL 244.771176 88.559545 \nL 245.129461 85.653833 \nL 245.487747 89.116375 \nL 245.846032 85.458374 \nL 246.204318 85.794463 \nL 246.562604 88.264355 \nL 246.920889 89.824381 \nL 247.279175 73.887171 \nL 247.637461 90.668776 \nL 247.995746 85.980423 \nL 248.354032 86.807862 \nL 248.712317 88.363899 \nL 249.070603 81.921581 \nL 249.428889 88.311484 \nL 249.787174 81.351537 \nL 250.14546 87.463229 \nL 250.503746 90.844169 \nL 250.862031 82.562508 \nL 251.220317 94.522998 \nL 251.578602 88.763467 \nL 252.295174 84.309434 \nL 252.653459 85.124653 \nL 253.011745 86.403006 \nL 253.37003 91.813617 \nL 253.728316 92.154081 \nL 254.086602 90.788462 \nL 254.444887 90.25801 \nL 254.803173 90.144779 \nL 255.161459 86.167871 \nL 255.519744 88.937967 \nL 255.87803 83.697933 \nL 256.236315 85.685441 \nL 256.594601 33.385336 \nL 257.311172 83.364122 \nL 257.669458 85.947092 \nL 258.027744 89.859423 \nL 258.386029 83.91171 \nL 258.744315 89.564405 \nL 259.1026 88.180227 \nL 259.460886 91.043273 \nL 259.819172 90.248445 \nL 260.177457 85.690706 \nL 260.894029 87.971781 \nL 261.252314 86.989142 \nL 261.6106 92.810081 \nL 261.968885 91.323414 \nL 262.327171 87.886387 \nL 262.685457 89.837074 \nL 263.043742 85.802718 \nL 263.402028 87.697753 \nL 264.118599 86.174501 \nL 264.476885 88.061774 \nL 264.83517 88.38446 \nL 265.193456 83.072411 \nL 265.551742 86.284657 \nL 265.910027 82.507639 \nL 266.268313 83.76394 \nL 266.626599 87.921947 \nL 266.984884 84.105642 \nL 267.34317 91.310094 \nL 267.701455 82.727417 \nL 268.418027 92.11063 \nL 268.776312 88.54706 \nL 269.134598 89.028231 \nL 269.492884 84.90822 \nL 269.851169 87.515257 \nL 270.209455 82.064464 \nL 270.56774 87.107179 \nL 271.284312 84.726419 \nL 271.642597 88.029159 \nL 272.000883 83.059045 \nL 272.359168 81.44781 \nL 272.717454 88.218843 \nL 273.07574 83.987367 \nL 273.434025 85.961568 \nL 273.792311 85.314507 \nL 274.150597 87.703534 \nL 274.508882 86.248676 \nL 274.867168 79.130778 \nL 275.225453 78.817939 \nL 275.583739 89.949851 \nL 275.942025 94.287223 \nL 276.30031 85.447264 \nL 276.658596 84.074481 \nL 277.016882 85.247948 \nL 277.375167 82.513405 \nL 277.733453 87.495233 \nL 278.091738 86.487895 \nL 278.450024 60.731422 \nL 278.80831 75.563192 \nL 279.166595 74.422551 \nL 279.524881 90.684349 \nL 279.883167 81.606432 \nL 280.241452 92.696495 \nL 280.958023 77.777898 \nL 281.316309 84.39816 \nL 281.674595 83.128193 \nL 282.03288 84.928628 \nL 282.391166 90.336545 \nL 282.749452 87.984189 \nL 283.107737 89.195862 \nL 283.466023 86.424733 \nL 283.824308 89.294983 \nL 284.182594 86.325225 \nL 284.54088 86.427192 \nL 284.899165 83.372756 \nL 285.615737 88.664357 \nL 285.974022 84.286139 \nL 286.332308 89.455535 \nL 286.690593 74.466596 \nL 287.048879 85.85813 \nL 287.407165 88.121673 \nL 287.76545 84.479698 \nL 288.123736 82.695744 \nL 288.482022 89.882471 \nL 288.840307 84.219577 \nL 289.198593 87.931856 \nL 289.556878 83.110916 \nL 289.915164 82.065727 \nL 290.27345 88.211281 \nL 290.631735 88.500441 \nL 290.990021 86.066815 \nL 291.348306 89.570771 \nL 291.706592 87.45367 \nL 292.064878 83.578472 \nL 292.423163 88.587913 \nL 292.781449 80.392332 \nL 293.139735 86.638741 \nL 293.49802 90.80007 \nL 293.856306 84.199194 \nL 294.214591 83.896369 \nL 294.572877 80.755619 \nL 294.931163 91.189425 \nL 295.289448 87.846574 \nL 295.647734 86.072258 \nL 296.00602 85.774046 \nL 296.722591 92.964448 \nL 297.080876 81.226014 \nL 297.439162 85.230508 \nL 297.797448 83.671721 \nL 298.155733 87.505887 \nL 298.514019 90.031445 \nL 298.872305 87.246897 \nL 299.23059 89.983469 \nL 299.588876 81.210118 \nL 299.947161 83.161073 \nL 300.305447 85.738933 \nL 300.663733 85.457117 \nL 301.022018 71.13359 \nL 301.380304 87.414473 \nL 301.73859 89.608077 \nL 302.096875 85.449151 \nL 302.455161 90.228996 \nL 302.813446 87.888033 \nL 303.171732 73.697236 \nL 303.530018 80.834129 \nL 303.888303 85.390356 \nL 304.246589 84.157219 \nL 304.604875 80.04485 \nL 304.96316 88.317886 \nL 305.321446 92.412594 \nL 305.679731 85.50694 \nL 306.038017 86.701334 \nL 306.396303 84.965979 \nL 306.754588 85.904258 \nL 307.112874 76.031408 \nL 307.47116 83.389731 \nL 307.829445 85.211756 \nL 308.187731 87.931999 \nL 308.546016 85.570347 \nL 308.904302 86.360494 \nL 309.262588 79.666258 \nL 309.620873 87.32713 \nL 309.979159 85.989213 \nL 310.337444 85.181791 \nL 310.69573 87.984913 \nL 311.054016 86.702375 \nL 311.412301 88.597003 \nL 311.770587 86.24015 \nL 312.128873 88.948334 \nL 312.487158 81.873272 \nL 312.845444 87.158169 \nL 313.203729 88.738566 \nL 313.562015 86.65918 \nL 313.920301 87.291276 \nL 314.278586 90.139778 \nL 314.636872 77.859027 \nL 314.995158 83.692437 \nL 315.353443 82.970536 \nL 315.711729 89.814191 \nL 316.070014 87.426439 \nL 316.4283 86.989176 \nL 316.786586 84.963041 \nL 317.144871 71.575839 \nL 317.503157 86.019002 \nL 317.861443 84.20589 \nL 318.219728 84.026644 \nL 318.578014 87.599836 \nL 318.936299 85.435408 \nL 319.294585 84.803784 \nL 319.652871 85.025041 \nL 320.011156 85.891092 \nL 320.369442 85.188313 \nL 321.086013 88.128038 \nL 321.444299 84.113776 \nL 321.802584 87.892872 \nL 322.16087 89.825594 \nL 322.519156 86.338339 \nL 322.877441 85.566885 \nL 323.235727 85.989511 \nL 323.594013 80.877497 \nL 323.952298 84.028975 \nL 324.310584 79.110459 \nL 324.668869 80.289087 \nL 325.027155 86.800271 \nL 325.385441 82.252212 \nL 325.743726 86.675452 \nL 326.102012 82.577347 \nL 326.460298 84.895646 \nL 326.818583 81.561324 \nL 327.176869 85.208483 \nL 327.535154 86.907519 \nL 327.89344 87.543589 \nL 328.251726 81.690794 \nL 328.610011 86.175609 \nL 328.968297 84.939925 \nL 329.326582 88.499197 \nL 329.684868 85.497625 \nL 330.043154 90.029802 \nL 330.401439 73.510728 \nL 330.759725 87.781515 \nL 331.118011 79.460773 \nL 331.476296 87.95914 \nL 331.834582 75.227318 \nL 332.192867 84.219106 \nL 332.551153 86.218213 \nL 332.909439 86.51035 \nL 333.267724 82.565325 \nL 333.62601 84.959329 \nL 333.984296 84.766046 \nL 334.342581 78.920613 \nL 334.700867 83.148742 \nL 335.059152 82.224892 \nL 335.417438 84.348835 \nL 335.775724 61.254432 \nL 336.134009 75.375781 \nL 336.492295 82.805448 \nL 336.850581 87.102015 \nL 337.208866 78.918866 \nL 337.567152 87.941025 \nL 338.283723 80.764453 \nL 338.642009 82.269577 \nL 339.000294 88.813281 \nL 339.35858 88.776422 \nL 339.716866 90.211516 \nL 340.075151 83.867183 \nL 340.433437 80.131132 \nL 340.791722 82.04123 \nL 341.150008 81.162538 \nL 341.508294 86.838389 \nL 341.866579 83.973694 \nL 342.224865 86.567117 \nL 342.583151 86.083738 \nL 342.941436 85.404455 \nL 343.299722 68.988933 \nL 343.658007 81.120893 \nL 344.016293 86.233475 \nL 344.374579 77.810932 \nL 344.732864 88.839772 \nL 345.09115 81.893297 \nL 345.449435 85.522677 \nL 345.807721 62.021157 \nL 346.166007 80.681326 \nL 346.524292 85.102639 \nL 346.882578 85.075714 \nL 347.240864 87.811884 \nL 347.599149 89.544835 \nL 347.957435 86.910358 \nL 348.31572 82.030101 \nL 348.674006 84.912506 \nL 349.032292 83.394316 \nL 349.390577 81.044532 \nL 349.748863 82.73549 \nL 350.107149 86.926679 \nL 350.465434 88.285421 \nL 350.82372 88.35407 \nL 351.182005 84.355934 \nL 351.540291 85.655573 \nL 351.898577 83.941245 \nL 352.256862 73.544698 \nL 352.615148 85.190495 \nL 352.973434 82.412459 \nL 353.690005 88.219844 \nL 354.04829 85.703115 \nL 354.406576 85.632811 \nL 354.764862 87.991622 \nL 355.123147 84.665656 \nL 355.481433 79.445948 \nL 355.839719 84.802704 \nL 356.198004 83.709357 \nL 356.55629 83.873408 \nL 356.914575 84.231037 \nL 357.272861 79.496676 \nL 357.631147 86.552251 \nL 357.989432 86.230604 \nL 358.706004 83.15618 \nL 359.064289 85.469171 \nL 359.422575 83.634555 \nL 359.78086 85.816549 \nL 360.139146 85.77982 \nL 360.497432 79.408462 \nL 360.855717 93.792677 \nL 361.214003 86.538288 \nL 361.572289 86.396333 \nL 361.930574 83.731481 \nL 362.28886 85.09918 \nL 362.647145 83.312069 \nL 363.005431 67.550611 \nL 363.363717 87.630784 \nL 363.722002 80.141358 \nL 364.080288 84.947161 \nL 364.438573 87.508016 \nL 364.796859 88.331129 \nL 365.155145 83.26697 \nL 365.51343 84.752999 \nL 365.871716 83.191405 \nL 366.230002 87.577349 \nL 366.588287 78.266654 \nL 367.304858 90.276632 \nL 367.663144 86.112053 \nL 368.02143 84.900491 \nL 368.379715 87.904966 \nL 368.738001 85.542713 \nL 369.096287 86.646316 \nL 369.454572 83.390076 \nL 369.812858 85.45346 \nL 370.171143 80.069937 \nL 370.529429 90.150395 \nL 370.887715 88.859982 \nL 371.246 83.297529 \nL 371.604286 87.347567 \nL 371.962572 76.096914 \nL 372.320857 86.056713 \nL 372.679143 87.566489 \nL 373.395714 82.642867 \nL 373.754 84.014313 \nL 374.112285 82.035499 \nL 374.470571 88.111176 \nL 374.828857 81.726442 \nL 375.187142 79.982779 \nL 375.545428 84.512058 \nL 375.903713 84.84317 \nL 376.261999 83.980996 \nL 376.620285 87.346363 \nL 376.97857 86.158869 \nL 377.336856 86.066634 \nL 377.695142 81.542396 \nL 378.053427 86.563464 \nL 378.411713 89.93905 \nL 378.769998 84.268399 \nL 379.128284 82.203462 \nL 379.844855 88.635931 \nL 380.203141 70.814664 \nL 380.561427 84.361463 \nL 380.919712 88.788728 \nL 381.277998 84.909235 \nL 381.636283 87.254252 \nL 381.994569 87.088516 \nL 382.352855 84.003091 \nL 383.427711 87.286113 \nL 383.785997 86.054073 \nL 384.144283 85.947619 \nL 384.502568 88.120348 \nL 384.860854 86.202877 \nL 385.21914 88.43667 \nL 385.577425 84.128592 \nL 385.935711 87.512264 \nL 386.293996 87.293124 \nL 386.652282 75.494233 \nL 387.010568 83.529633 \nL 387.368853 86.471485 \nL 387.727139 84.675591 \nL 388.085425 85.223061 \nL 388.44371 83.166886 \nL 388.801996 81.798393 \nL 389.160281 82.308355 \nL 389.518567 89.185108 \nL 390.235138 83.382522 \nL 390.593424 88.908584 \nL 390.95171 87.364602 \nL 391.309995 88.137521 \nL 391.668281 79.101221 \nL 392.026566 79.479985 \nL 392.384852 82.01172 \nL 392.743138 83.411294 \nL 393.101423 88.208081 \nL 393.459709 82.358163 \nL 393.817995 86.681126 \nL 394.17628 77.375497 \nL 394.534566 81.953211 \nL 395.251137 85.85912 \nL 395.609423 81.980603 \nL 395.967708 84.350797 \nL 396.325994 90.125136 \nL 396.68428 86.915264 \nL 397.042565 79.379065 \nL 397.400851 86.275878 \nL 397.759136 88.486821 \nL 398.117422 85.01351 \nL 398.475708 88.675185 \nL 398.833993 87.075537 \nL 399.192279 80.434221 \nL 399.550565 88.097205 \nL 399.90885 79.332844 \nL 400.267136 89.679243 \nL 400.983707 85.650308 \nL 401.341993 85.201952 \nL 401.700278 80.906995 \nL 402.058564 83.156012 \nL 402.416849 88.795696 \nL 402.775135 87.855528 \nL 403.133421 89.968605 \nL 403.491706 87.286119 \nL 403.849992 80.753476 \nL 404.208278 82.501875 \nL 404.566563 81.750411 \nL 404.924849 85.088593 \nL 405.283134 76.706068 \nL 405.64142 88.695855 \nL 405.999706 90.330772 \nL 406.716277 83.805679 \nL 407.074563 83.601236 \nL 407.432848 89.220891 \nL 407.791134 88.910745 \nL 408.149419 87.739639 \nL 408.507705 85.794545 \nL 408.865991 81.572827 \nL 409.224276 82.456694 \nL 409.582562 86.810071 \nL 409.940848 88.603994 \nL 410.299133 85.601373 \nL 410.657419 89.223211 \nL 411.015704 83.979119 \nL 411.37399 82.139775 \nL 411.732276 81.417683 \nL 412.090561 87.378786 \nL 412.448847 84.427151 \nL 412.807133 84.53758 \nL 413.165418 88.224207 \nL 413.523704 71.706299 \nL 413.881989 90.697325 \nL 414.240275 93.451714 \nL 414.598561 83.652708 \nL 414.956846 86.661176 \nL 415.315132 84.19251 \nL 415.673418 87.794943 \nL 416.031703 89.809982 \nL 416.389989 78.812418 \nL 416.748274 84.32287 \nL 417.10656 85.53961 \nL 417.464846 89.478089 \nL 417.823131 88.378099 \nL 418.181417 89.821207 \nL 418.539702 80.975579 \nL 418.897988 87.116355 \nL 419.256274 87.209153 \nL 419.614559 86.694584 \nL 419.972845 88.692245 \nL 420.331131 87.233282 \nL 420.689416 83.984966 \nL 421.047702 88.497832 \nL 421.405987 71.100373 \nL 421.764273 82.064857 \nL 422.122559 87.970455 \nL 422.480844 89.666875 \nL 423.197416 85.415465 \nL 423.555701 86.428512 \nL 423.913987 86.073875 \nL 424.272272 89.18967 \nL 424.630558 91.286328 \nL 424.988844 86.197985 \nL 425.347129 84.86785 \nL 425.705415 80.93294 \nL 426.063701 91.891948 \nL 426.421986 84.777565 \nL 426.780272 86.660854 \nL 427.138557 84.564786 \nL 427.496843 84.795551 \nL 427.855129 88.382661 \nL 428.213414 89.096903 \nL 428.5717 88.600787 \nL 428.929986 76.757027 \nL 429.288271 86.028723 \nL 429.646557 84.866231 \nL 430.004842 88.122519 \nL 430.363128 87.33214 \nL 430.721414 78.452096 \nL 431.079699 88.997026 \nL 431.437985 88.702314 \nL 431.796271 85.242128 \nL 432.154556 85.05794 \nL 432.512842 85.070695 \nL 432.871127 86.951882 \nL 433.229413 76.223283 \nL 433.945984 87.359973 \nL 434.30427 86.658333 \nL 434.662556 89.947153 \nL 435.020841 87.336122 \nL 435.379127 87.342408 \nL 435.737412 86.395569 \nL 436.095698 87.010906 \nL 436.812269 91.253363 \nL 437.52884 87.520171 \nL 438.245412 78.819342 \nL 438.603697 80.335226 \nL 438.961983 68.144756 \nL 439.320269 86.867068 \nL 439.678554 86.464428 \nL 440.03684 85.02474 \nL 440.395125 85.344938 \nL 440.753411 83.998899 \nL 441.111697 90.265454 \nL 441.469982 90.314661 \nL 441.828268 92.172779 \nL 442.186554 91.085998 \nL 442.544839 83.008339 \nL 443.26141 87.290631 \nL 443.619696 81.233702 \nL 443.977982 84.444903 \nL 444.336267 94.97923 \nL 444.694553 86.502667 \nL 445.052839 82.359071 \nL 445.411124 86.659556 \nL 445.76941 86.840458 \nL 446.127695 85.809083 \nL 446.485981 86.871206 \nL 446.844267 85.207578 \nL 447.560838 91.437276 \nL 447.919124 81.107131 \nL 448.277409 86.381214 \nL 448.635695 82.537855 \nL 448.99398 87.315103 \nL 449.352266 86.175763 \nL 449.710552 82.774003 \nL 450.068837 86.110956 \nL 450.427123 86.925601 \nL 450.785409 83.599765 \nL 451.143694 91.856031 \nL 451.50198 88.715419 \nL 451.860265 90.283537 \nL 452.218551 80.54498 \nL 452.576837 82.451122 \nL 452.935122 86.396285 \nL 453.293408 83.06743 \nL 453.651694 89.156141 \nL 454.009979 87.004448 \nL 454.368265 93.982644 \nL 454.72655 85.87553 \nL 455.084836 86.498641 \nL 455.443122 86.72672 \nL 455.801407 84.384014 \nL 456.159693 88.042172 \nL 456.517978 83.769618 \nL 456.876264 83.536044 \nL 457.23455 89.861078 \nL 457.592835 86.37781 \nL 457.951121 85.753972 \nL 458.309407 88.534426 \nL 458.667692 86.398468 \nL 459.025978 89.721323 \nL 459.742549 85.146474 \nL 460.100835 88.090298 \nL 460.45912 85.206943 \nL 460.817406 85.477493 \nL 461.175692 87.915283 \nL 461.533977 79.745892 \nL 461.892263 88.847073 \nL 462.250548 81.339812 \nL 462.96712 87.486086 \nL 463.325405 88.539902 \nL 463.683691 84.901237 \nL 464.041977 87.523736 \nL 464.400262 91.163197 \nL 464.758548 88.830756 \nL 465.116833 88.959356 \nL 465.475119 90.045793 \nL 465.833405 84.55414 \nL 466.19169 84.778095 \nL 466.549976 83.589527 \nL 466.908262 85.218904 \nL 467.266547 90.685723 \nL 467.624833 88.627834 \nL 467.983118 90.553753 \nL 468.341404 91.319855 \nL 468.69969 81.34739 \nL 469.057975 85.288607 \nL 469.416261 91.636314 \nL 469.774547 81.829218 \nL 470.132832 85.40079 \nL 470.491118 90.359609 \nL 470.849403 89.232867 \nL 471.207689 81.68561 \nL 471.565975 88.523052 \nL 471.92426 78.129435 \nL 472.282546 83.905353 \nL 472.640832 80.432085 \nL 472.999117 87.427323 \nL 473.715688 83.797939 \nL 474.073974 83.17282 \nL 474.43226 88.576442 \nL 474.790545 89.739975 \nL 475.148831 81.578254 \nL 475.507116 90.644799 \nL 475.865402 77.600554 \nL 476.223688 83.635595 \nL 476.581973 85.228056 \nL 476.940259 75.324026 \nL 477.298545 86.119563 \nL 477.65683 92.264307 \nL 478.015116 85.396678 \nL 478.373401 87.089143 \nL 478.731687 84.748353 \nL 479.089973 87.309618 \nL 479.448258 86.84092 \nL 479.806544 85.948314 \nL 480.16483 88.538356 \nL 480.523115 89.964021 \nL 480.881401 83.109226 \nL 481.239686 84.006037 \nL 481.597972 87.31923 \nL 481.956258 85.162334 \nL 482.314543 85.390466 \nL 482.672829 86.100218 \nL 483.031115 86.052309 \nL 483.3894 80.389602 \nL 483.747686 84.515313 \nL 484.105971 86.318689 \nL 484.464257 89.217728 \nL 484.822543 83.916197 \nL 485.180828 87.290273 \nL 485.539114 88.867307 \nL 485.8974 87.398903 \nL 486.255685 77.629322 \nL 486.613971 83.159255 \nL 486.972256 80.179309 \nL 487.330542 83.708594 \nL 487.688828 82.070474 \nL 488.047113 83.99139 \nL 488.405399 86.885695 \nL 488.763685 83.325094 \nL 489.12197 88.825954 \nL 489.838541 85.118152 \nL 490.196827 86.417459 \nL 490.555113 84.474243 \nL 490.913398 85.44315 \nL 491.271684 84.121259 \nL 491.62997 87.126771 \nL 491.988255 88.173035 \nL 492.704826 75.384303 \nL 493.063112 90.594394 \nL 493.421398 80.899658 \nL 493.779683 87.393506 \nL 494.137969 90.694764 \nL 494.496254 82.662564 \nL 494.85454 84.655584 \nL 495.212826 85.974967 \nL 495.571111 88.24211 \nL 495.929397 83.235057 \nL 496.287683 82.183376 \nL 496.645968 85.478655 \nL 497.004254 91.043512 \nL 497.362539 75.562871 \nL 497.720825 82.520085 \nL 498.079111 86.38945 \nL 498.795682 88.115839 \nL 499.153968 79.386258 \nL 499.512253 85.823843 \nL 499.870539 83.846971 \nL 500.228824 83.810887 \nL 500.58711 84.934757 \nL 500.945396 79.719134 \nL 501.303681 85.921439 \nL 501.661967 85.864787 \nL 502.020253 90.328345 \nL 502.378538 82.824969 \nL 502.736824 90.309889 \nL 503.095109 86.863302 \nL 503.453395 87.895819 \nL 503.811681 82.868117 \nL 504.169966 83.027384 \nL 504.528252 87.706853 \nL 504.886538 85.820574 \nL 505.244823 80.686068 \nL 505.603109 86.033623 \nL 505.961394 84.737509 \nL 506.31968 86.345704 \nL 506.677966 81.948412 \nL 507.036251 86.600724 \nL 507.394537 83.861922 \nL 507.752823 85.467545 \nL 508.111108 83.632156 \nL 508.469394 86.957391 \nL 508.827679 84.941144 \nL 509.185965 86.534006 \nL 509.544251 80.979073 \nL 509.902536 86.769469 \nL 510.260822 87.981903 \nL 510.619107 88.077051 \nL 510.977393 86.027608 \nL 511.335679 86.029933 \nL 511.693964 85.724849 \nL 512.05225 87.22468 \nL 512.410536 89.974028 \nL 512.768821 80.455375 \nL 513.127107 84.263299 \nL 513.485392 81.848126 \nL 513.843678 82.791417 \nL 514.201964 83.403667 \nL 514.560249 85.338905 \nL 514.918535 88.03363 \nL 515.276821 84.607055 \nL 515.635106 87.240699 \nL 515.993392 82.637807 \nL 516.709963 86.395909 \nL 517.068249 83.441465 \nL 517.426534 89.219411 \nL 517.78482 84.382155 \nL 518.143106 84.458602 \nL 518.501391 83.518533 \nL 518.859677 84.551997 \nL 519.217962 84.831375 \nL 519.576248 83.535152 \nL 519.934534 84.914957 \nL 520.292819 85.2063 \nL 520.651105 87.364411 \nL 521.009391 86.580459 \nL 521.367676 88.287768 \nL 521.725962 78.051175 \nL 522.084247 83.339472 \nL 522.442533 80.319106 \nL 522.800819 86.351432 \nL 523.159104 89.064076 \nL 523.51739 85.166092 \nL 524.233961 87.734552 \nL 524.592247 84.326582 \nL 524.950532 84.354619 \nL 525.308818 84.184439 \nL 525.667104 87.305327 \nL 526.025389 85.328856 \nL 526.383675 87.012532 \nL 526.741961 75.136291 \nL 527.458532 87.061334 \nL 527.816817 80.387421 \nL 528.175103 85.437614 \nL 528.533389 86.966662 \nL 528.891674 86.28125 \nL 529.24996 82.597656 \nL 529.966531 84.354616 \nL 530.324817 87.592989 \nL 530.683102 85.426937 \nL 531.041388 86.341281 \nL 531.399674 80.270407 \nL 531.757959 84.900051 \nL 532.116245 86.694529 \nL 532.47453 85.087493 \nL 532.832816 84.985466 \nL 533.191102 86.407985 \nL 533.549387 84.146055 \nL 533.907673 84.754303 \nL 534.265959 88.546476 \nL 534.624244 87.59804 \nL 534.98253 83.87634 \nL 535.340815 84.668416 \nL 535.699101 84.722573 \nL 536.057387 76.71945 \nL 536.415672 86.802015 \nL 537.132244 84.930888 \nL 537.490529 86.507529 \nL 537.848815 87.272003 \nL 538.2071 84.404496 \nL 538.923672 88.351835 \nL 539.281957 87.036002 \nL 539.640243 87.025231 \nL 539.998529 81.079859 \nL 540.7151 86.05757 \nL 541.431671 85.914113 \nL 541.789957 86.578025 \nL 542.148242 85.0444 \nL 542.506528 89.060931 \nL 542.864814 88.147515 \nL 543.223099 85.025162 \nL 543.581385 85.74134 \nL 543.93967 84.23221 \nL 544.297956 83.621514 \nL 544.656242 87.023041 \nL 545.014527 82.322894 \nL 545.372813 89.053929 \nL 545.731099 79.579515 \nL 546.089384 89.015803 \nL 546.44767 88.070352 \nL 546.805955 80.135064 \nL 547.164241 87.052236 \nL 547.522527 84.579967 \nL 547.880812 86.437493 \nL 548.239098 83.546433 \nL 548.597383 88.013734 \nL 548.955669 87.487892 \nL 549.313955 87.49398 \nL 549.67224 89.079021 \nL 550.030526 86.043505 \nL 550.388812 86.889337 \nL 550.747097 89.994779 \nL 551.105383 86.956167 \nL 551.463668 80.50929 \nL 551.821954 85.898691 \nL 552.18024 79.428769 \nL 552.538525 85.211197 \nL 552.896811 85.215379 \nL 553.255097 85.542949 \nL 553.613382 89.131032 \nL 553.971668 82.655071 \nL 554.329953 88.574097 \nL 554.688239 74.461461 \nL 555.046525 90.917104 \nL 555.40481 85.765851 \nL 555.763096 89.472791 \nL 556.121382 83.150184 \nL 556.479667 82.214664 \nL 556.837953 85.191242 \nL 557.196238 82.195885 \nL 557.554524 88.739344 \nL 557.91281 88.127242 \nL 558.271095 84.592157 \nL 558.629381 87.824578 \nL 558.987667 92.691034 \nL 559.345952 86.299178 \nL 559.704238 87.889001 \nL 560.062523 91.043845 \nL 560.420809 90.959354 \nL 560.779095 89.181287 \nL 561.13738 84.986186 \nL 561.495666 87.46476 \nL 561.853952 83.890134 \nL 562.212237 78.986496 \nL 562.570523 87.954289 \nL 562.928808 86.581865 \nL 563.287094 88.393473 \nL 563.64538 88.06845 \nL 564.003665 90.786726 \nL 564.361951 90.558176 \nL 564.720237 87.502975 \nL 565.078522 82.26422 \nL 565.436808 79.934937 \nL 566.153379 90.265311 \nL 566.511665 89.346441 \nL 566.86995 89.573268 \nL 567.228236 92.182943 \nL 567.586521 91.310111 \nL 567.944807 84.383042 \nL 568.303093 87.388677 \nL 568.661378 87.535304 \nL 569.019664 88.307255 \nL 569.37795 84.866651 \nL 569.736235 89.407295 \nL 570.094521 80.194095 \nL 570.452806 81.593984 \nL 570.811092 85.083012 \nL 571.169378 86.530158 \nL 571.527663 70.286924 \nL 571.885949 84.721759 \nL 572.244235 91.514985 \nL 572.60252 91.799602 \nL 572.960806 89.704289 \nL 573.319091 84.395984 \nL 573.677377 89.476078 \nL 574.035663 87.715852 \nL 574.393948 67.15311 \nL 574.752234 82.434926 \nL 575.11052 81.749386 \nL 575.468805 82.465424 \nL 575.827091 86.069914 \nL 576.185376 86.974687 \nL 576.543662 87.028297 \nL 576.901948 83.540978 \nL 577.260233 86.569389 \nL 577.976805 85.228387 \nL 578.33509 85.60393 \nL 578.693376 87.436476 \nL 579.051661 84.440916 \nL 579.409947 88.900123 \nL 579.768233 86.785265 \nL 580.126518 83.166301 \nL 580.484804 82.108265 \nL 580.84309 81.489528 \nL 581.201375 85.799328 \nL 581.559661 84.962244 \nL 581.917946 85.047018 \nL 582.276232 87.270725 \nL 582.634518 91.974711 \nL 582.992803 87.601481 \nL 583.351089 87.823352 \nL 583.709374 84.489473 \nL 584.06766 88.935679 \nL 584.425946 88.529141 \nL 585.142517 90.59734 \nL 585.500803 87.519216 \nL 585.859088 85.432985 \nL 586.217374 84.318055 \nL 586.575659 87.410271 \nL 586.933945 88.186038 \nL 587.292231 79.6045 \nL 587.650516 85.683605 \nL 588.008802 80.812108 \nL 588.725373 84.150376 \nL 589.083659 89.255813 \nL 589.441944 87.430059 \nL 589.80023 86.657281 \nL 590.158516 88.267028 \nL 590.516801 84.636792 \nL 590.875087 82.981689 \nL 591.233373 85.870608 \nL 591.591658 83.839564 \nL 591.949944 80.23974 \nL 592.308229 87.000609 \nL 592.666515 81.931143 \nL 593.024801 87.351934 \nL 593.383086 84.4233 \nL 594.099658 86.524518 \nL 594.457943 88.707444 \nL 594.816229 87.260912 \nL 595.174514 90.487351 \nL 595.5328 87.017055 \nL 595.891086 86.849852 \nL 596.249371 76.557072 \nL 596.607657 84.081709 \nL 596.965943 83.65174 \nL 597.324228 81.077984 \nL 597.682514 89.173377 \nL 598.040799 85.654528 \nL 598.399085 87.805247 \nL 598.757371 85.897508 \nL 599.115656 89.368102 \nL 599.473942 90.41085 \nL 599.832228 92.979896 \nL 600.907084 81.886616 \nL 601.26537 83.353096 \nL 601.623656 83.046584 \nL 601.981941 88.107234 \nL 602.698512 91.391571 \nL 603.056798 87.805986 \nL 603.415084 82.831752 \nL 603.773369 89.045794 \nL 604.131655 85.628716 \nL 604.489941 86.510539 \nL 604.848226 85.574939 \nL 605.206512 88.235193 \nL 605.564797 89.909187 \nL 605.923083 82.830622 \nL 606.281369 88.339353 \nL 606.99794 82.920362 \nL 607.356226 85.38984 \nL 607.714511 84.61432 \nL 608.072797 88.850517 \nL 608.431082 80.502154 \nL 608.789368 90.600468 \nL 609.505939 81.804012 \nL 609.864225 84.858472 \nL 610.222511 84.114313 \nL 610.580796 82.782653 \nL 610.939082 87.104805 \nL 611.655653 80.739447 \nL 612.372224 88.142711 \nL 612.73051 88.358759 \nL 613.088796 93.246214 \nL 613.805367 85.491971 \nL 614.163652 88.491189 \nL 614.521938 85.056157 \nL 614.880224 79.514055 \nL 615.238509 87.320167 \nL 615.596795 74.694828 \nL 615.955081 89.399351 \nL 616.313366 81.961633 \nL 616.671652 80.771126 \nL 617.029937 87.882138 \nL 617.388223 86.692974 \nL 617.746509 87.8899 \nL 618.104794 90.605511 \nL 618.46308 86.526237 \nL 618.821366 85.356051 \nL 619.179651 85.241167 \nL 619.537937 81.732719 \nL 619.896222 82.892182 \nL 620.254508 88.377058 \nL 620.612794 87.044507 \nL 620.971079 88.018543 \nL 621.329365 86.742387 \nL 621.68765 87.173011 \nL 622.045936 81.329959 \nL 622.404222 91.401282 \nL 622.762507 87.516165 \nL 623.120793 74.07451 \nL 623.479079 89.900945 \nL 623.837364 91.035775 \nL 624.19565 90.695866 \nL 624.553935 87.982249 \nL 624.912221 87.896239 \nL 625.270507 87.212197 \nL 625.628792 86.247037 \nL 625.987078 88.422339 \nL 626.345364 86.288141 \nL 626.703649 85.746903 \nL 627.061935 90.366564 \nL 627.42022 79.427682 \nL 628.136792 85.161591 \nL 628.495077 85.777783 \nL 629.211649 87.906021 \nL 629.569934 87.849405 \nL 629.92822 90.100535 \nL 630.286505 84.924119 \nL 630.644791 87.540215 \nL 631.003077 72.628454 \nL 631.361362 85.370273 \nL 631.719648 86.534632 \nL 632.077934 86.783452 \nL 632.436219 83.919367 \nL 632.794505 85.663264 \nL 633.15279 83.710421 \nL 633.511076 88.75201 \nL 633.869362 86.382201 \nL 634.227647 88.138057 \nL 634.585933 89.207827 \nL 634.944219 87.686382 \nL 635.302504 87.926775 \nL 635.66079 82.665499 \nL 636.019075 87.167203 \nL 636.377361 85.630319 \nL 636.735647 85.974822 \nL 637.093932 91.178354 \nL 637.452218 84.30544 \nL 637.810504 86.875774 \nL 638.168789 75.506725 \nL 638.527075 87.959333 \nL 638.88536 88.002058 \nL 639.243646 85.834686 \nL 639.601932 88.263984 \nL 639.960217 82.898451 \nL 640.318503 88.621811 \nL 640.676788 76.886181 \nL 641.035074 87.167587 \nL 641.39336 86.44578 \nL 642.109931 87.964883 \nL 642.468217 89.702501 \nL 643.184788 82.693128 \nL 644.259645 88.516102 \nL 644.61793 87.360046 \nL 644.976216 80.525351 \nL 645.334502 86.738297 \nL 645.692787 87.501202 \nL 646.051073 81.632293 \nL 646.409358 91.056221 \nL 646.767644 89.462034 \nL 647.12593 89.813044 \nL 647.842501 83.239208 \nL 648.200787 86.120537 \nL 648.559072 85.31954 \nL 648.917358 83.074645 \nL 649.275643 86.648848 \nL 649.633929 82.426947 \nL 649.992215 87.572986 \nL 650.3505 83.770355 \nL 650.708786 89.591346 \nL 651.067072 82.747595 \nL 651.425357 88.130503 \nL 651.783643 84.791094 \nL 652.141928 88.56285 \nL 652.500214 86.667956 \nL 652.8585 75.243986 \nL 653.216785 87.969192 \nL 653.575071 90.834231 \nL 653.933357 87.044124 \nL 654.291642 89.605761 \nL 654.649928 87.020983 \nL 655.008213 78.542675 \nL 655.366499 85.561785 \nL 655.724785 82.428472 \nL 656.08307 87.637145 \nL 656.441356 88.59089 \nL 656.799642 85.13909 \nL 657.157927 84.579775 \nL 657.516213 89.023418 \nL 657.874498 86.214394 \nL 658.232784 87.807315 \nL 658.59107 93.313143 \nL 658.949355 80.968744 \nL 659.307641 86.59246 \nL 659.665926 83.057574 \nL 660.024212 81.923596 \nL 660.382498 86.855771 \nL 660.740783 85.747333 \nL 661.099069 90.866437 \nL 661.457355 86.003127 \nL 661.81564 84.952875 \nL 662.173926 87.593399 \nL 662.532211 74.394667 \nL 662.890497 84.925463 \nL 663.248783 86.924702 \nL 663.607068 87.356246 \nL 663.965354 88.259349 \nL 664.32364 83.722568 \nL 664.681925 82.42211 \nL 665.040211 85.039951 \nL 665.398496 84.126704 \nL 665.756782 87.853924 \nL 666.115068 86.033739 \nL 666.473353 89.719622 \nL 666.831639 84.909712 \nL 667.189925 88.25059 \nL 667.54821 83.995915 \nL 667.906496 85.898702 \nL 668.264781 86.079635 \nL 668.623067 83.765848 \nL 668.981353 89.890986 \nL 669.339638 83.331405 \nL 670.05621 88.81935 \nL 670.414495 87.952593 \nL 670.772781 85.432105 \nL 671.131066 84.959157 \nL 671.489352 88.670117 \nL 671.847638 86.4719 \nL 672.205923 78.219588 \nL 672.922495 90.137221 \nL 673.28078 89.27602 \nL 673.639066 86.062315 \nL 673.997351 86.636996 \nL 674.355637 90.664427 \nL 674.713923 76.238796 \nL 675.072208 86.685236 \nL 675.430494 84.992875 \nL 675.788779 88.405686 \nL 676.147065 82.939136 \nL 676.505351 85.552811 \nL 676.863636 86.717475 \nL 676.863636 86.717475 \n\" style=\"fill:none;stroke:#ff7f0e;stroke-linecap:square;stroke-width:1.5;\"/>\n   </g>\n   <g id=\"patch_3\">\n    <path d=\"M 37.7 279 \nL 37.7 7.2 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_4\">\n    <path d=\"M 707.3 279 \nL 707.3 7.2 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_5\">\n    <path d=\"M 37.7 279 \nL 707.3 279 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"patch_6\">\n    <path d=\"M 37.7 7.2 \nL 707.3 7.2 \n\" style=\"fill:none;stroke:#000000;stroke-linecap:square;stroke-linejoin:miter;stroke-width:0.8;\"/>\n   </g>\n   <g id=\"legend_1\">\n    <g id=\"patch_7\">\n     <path d=\"M 575.978125 274 \nL 700.3 274 \nQ 702.3 274 702.3 272 \nL 702.3 243.64375 \nQ 702.3 241.64375 700.3 241.64375 \nL 575.978125 241.64375 \nQ 573.978125 241.64375 573.978125 243.64375 \nL 573.978125 272 \nQ 573.978125 274 575.978125 274 \nz\n\" style=\"fill:#ffffff;opacity:0.8;stroke:#cccccc;stroke-linejoin:miter;\"/>\n    </g>\n    <g id=\"line2d_81\">\n     <path d=\"M 577.978125 249.742188 \nL 597.978125 249.742188 \n\" style=\"fill:none;stroke:#1f77b4;stroke-linecap:square;stroke-width:1.5;\"/>\n    </g>\n    <g id=\"line2d_82\"/>\n    <g id=\"text_13\">\n     <!-- Generator Loss -->\n     <g transform=\"translate(605.978125 253.242188)scale(0.1 -0.1)\">\n      <defs>\n       <path d=\"M 59.515625 10.40625 \nL 59.515625 29.984375 \nL 43.40625 29.984375 \nL 43.40625 38.09375 \nL 69.28125 38.09375 \nL 69.28125 6.78125 \nQ 63.578125 2.734375 56.6875 0.65625 \nQ 49.8125 -1.421875 42 -1.421875 \nQ 24.90625 -1.421875 15.25 8.5625 \nQ 5.609375 18.5625 5.609375 36.375 \nQ 5.609375 54.25 15.25 64.234375 \nQ 24.90625 74.21875 42 74.21875 \nQ 49.125 74.21875 55.546875 72.453125 \nQ 61.96875 70.703125 67.390625 67.28125 \nL 67.390625 56.78125 \nQ 61.921875 61.421875 55.765625 63.765625 \nQ 49.609375 66.109375 42.828125 66.109375 \nQ 29.4375 66.109375 22.71875 58.640625 \nQ 16.015625 51.171875 16.015625 36.375 \nQ 16.015625 21.625 22.71875 14.15625 \nQ 29.4375 6.6875 42.828125 6.6875 \nQ 48.046875 6.6875 52.140625 7.59375 \nQ 56.25 8.5 59.515625 10.40625 \nz\n\" id=\"DejaVuSans-71\"/>\n       <path d=\"M 56.203125 29.59375 \nL 56.203125 25.203125 \nL 14.890625 25.203125 \nQ 15.484375 15.921875 20.484375 11.0625 \nQ 25.484375 6.203125 34.421875 6.203125 \nQ 39.59375 6.203125 44.453125 7.46875 \nQ 49.3125 8.734375 54.109375 11.28125 \nL 54.109375 2.78125 \nQ 49.265625 0.734375 44.1875 -0.34375 \nQ 39.109375 -1.421875 33.890625 -1.421875 \nQ 20.796875 -1.421875 13.15625 6.1875 \nQ 5.515625 13.8125 5.515625 26.8125 \nQ 5.515625 40.234375 12.765625 48.109375 \nQ 20.015625 56 32.328125 56 \nQ 43.359375 56 49.78125 48.890625 \nQ 56.203125 41.796875 56.203125 29.59375 \nz\nM 47.21875 32.234375 \nQ 47.125 39.59375 43.09375 43.984375 \nQ 39.0625 48.390625 32.421875 48.390625 \nQ 24.90625 48.390625 20.390625 44.140625 \nQ 15.875 39.890625 15.1875 32.171875 \nz\n\" id=\"DejaVuSans-101\"/>\n       <path d=\"M 54.890625 33.015625 \nL 54.890625 0 \nL 45.90625 0 \nL 45.90625 32.71875 \nQ 45.90625 40.484375 42.875 44.328125 \nQ 39.84375 48.1875 33.796875 48.1875 \nQ 26.515625 48.1875 22.3125 43.546875 \nQ 18.109375 38.921875 18.109375 30.90625 \nL 18.109375 0 \nL 9.078125 0 \nL 9.078125 54.6875 \nL 18.109375 54.6875 \nL 18.109375 46.1875 \nQ 21.34375 51.125 25.703125 53.5625 \nQ 30.078125 56 35.796875 56 \nQ 45.21875 56 50.046875 50.171875 \nQ 54.890625 44.34375 54.890625 33.015625 \nz\n\" id=\"DejaVuSans-110\"/>\n       <path d=\"M 41.109375 46.296875 \nQ 39.59375 47.171875 37.8125 47.578125 \nQ 36.03125 48 33.890625 48 \nQ 26.265625 48 22.1875 43.046875 \nQ 18.109375 38.09375 18.109375 28.8125 \nL 18.109375 0 \nL 9.078125 0 \nL 9.078125 54.6875 \nL 18.109375 54.6875 \nL 18.109375 46.1875 \nQ 20.953125 51.171875 25.484375 53.578125 \nQ 30.03125 56 36.53125 56 \nQ 37.453125 56 38.578125 55.875 \nQ 39.703125 55.765625 41.0625 55.515625 \nz\n\" id=\"DejaVuSans-114\"/>\n       <path d=\"M 34.28125 27.484375 \nQ 23.390625 27.484375 19.1875 25 \nQ 14.984375 22.515625 14.984375 16.5 \nQ 14.984375 11.71875 18.140625 8.90625 \nQ 21.296875 6.109375 26.703125 6.109375 \nQ 34.1875 6.109375 38.703125 11.40625 \nQ 43.21875 16.703125 43.21875 25.484375 \nL 43.21875 27.484375 \nz\nM 52.203125 31.203125 \nL 52.203125 0 \nL 43.21875 0 \nL 43.21875 8.296875 \nQ 40.140625 3.328125 35.546875 0.953125 \nQ 30.953125 -1.421875 24.3125 -1.421875 \nQ 15.921875 -1.421875 10.953125 3.296875 \nQ 6 8.015625 6 15.921875 \nQ 6 25.140625 12.171875 29.828125 \nQ 18.359375 34.515625 30.609375 34.515625 \nL 43.21875 34.515625 \nL 43.21875 35.40625 \nQ 43.21875 41.609375 39.140625 45 \nQ 35.0625 48.390625 27.6875 48.390625 \nQ 23 48.390625 18.546875 47.265625 \nQ 14.109375 46.140625 10.015625 43.890625 \nL 10.015625 52.203125 \nQ 14.9375 54.109375 19.578125 55.046875 \nQ 24.21875 56 28.609375 56 \nQ 40.484375 56 46.34375 49.84375 \nQ 52.203125 43.703125 52.203125 31.203125 \nz\n\" id=\"DejaVuSans-97\"/>\n       <path d=\"M 18.3125 70.21875 \nL 18.3125 54.6875 \nL 36.8125 54.6875 \nL 36.8125 47.703125 \nL 18.3125 47.703125 \nL 18.3125 18.015625 \nQ 18.3125 11.328125 20.140625 9.421875 \nQ 21.96875 7.515625 27.59375 7.515625 \nL 36.8125 7.515625 \nL 36.8125 0 \nL 27.59375 0 \nQ 17.1875 0 13.234375 3.875 \nQ 9.28125 7.765625 9.28125 18.015625 \nL 9.28125 47.703125 \nL 2.6875 47.703125 \nL 2.6875 54.6875 \nL 9.28125 54.6875 \nL 9.28125 70.21875 \nz\n\" id=\"DejaVuSans-116\"/>\n       <path d=\"M 30.609375 48.390625 \nQ 23.390625 48.390625 19.1875 42.75 \nQ 14.984375 37.109375 14.984375 27.296875 \nQ 14.984375 17.484375 19.15625 11.84375 \nQ 23.34375 6.203125 30.609375 6.203125 \nQ 37.796875 6.203125 41.984375 11.859375 \nQ 46.1875 17.53125 46.1875 27.296875 \nQ 46.1875 37.015625 41.984375 42.703125 \nQ 37.796875 48.390625 30.609375 48.390625 \nz\nM 30.609375 56 \nQ 42.328125 56 49.015625 48.375 \nQ 55.71875 40.765625 55.71875 27.296875 \nQ 55.71875 13.875 49.015625 6.21875 \nQ 42.328125 -1.421875 30.609375 -1.421875 \nQ 18.84375 -1.421875 12.171875 6.21875 \nQ 5.515625 13.875 5.515625 27.296875 \nQ 5.515625 40.765625 12.171875 48.375 \nQ 18.84375 56 30.609375 56 \nz\n\" id=\"DejaVuSans-111\"/>\n       <path id=\"DejaVuSans-32\"/>\n       <path d=\"M 9.8125 72.90625 \nL 19.671875 72.90625 \nL 19.671875 8.296875 \nL 55.171875 8.296875 \nL 55.171875 0 \nL 9.8125 0 \nz\n\" id=\"DejaVuSans-76\"/>\n       <path d=\"M 44.28125 53.078125 \nL 44.28125 44.578125 \nQ 40.484375 46.53125 36.375 47.5 \nQ 32.28125 48.484375 27.875 48.484375 \nQ 21.1875 48.484375 17.84375 46.4375 \nQ 14.5 44.390625 14.5 40.28125 \nQ 14.5 37.15625 16.890625 35.375 \nQ 19.28125 33.59375 26.515625 31.984375 \nL 29.59375 31.296875 \nQ 39.15625 29.25 43.1875 25.515625 \nQ 47.21875 21.78125 47.21875 15.09375 \nQ 47.21875 7.46875 41.1875 3.015625 \nQ 35.15625 -1.421875 24.609375 -1.421875 \nQ 20.21875 -1.421875 15.453125 -0.5625 \nQ 10.6875 0.296875 5.421875 2 \nL 5.421875 11.28125 \nQ 10.40625 8.6875 15.234375 7.390625 \nQ 20.0625 6.109375 24.8125 6.109375 \nQ 31.15625 6.109375 34.5625 8.28125 \nQ 37.984375 10.453125 37.984375 14.40625 \nQ 37.984375 18.0625 35.515625 20.015625 \nQ 33.0625 21.96875 24.703125 23.78125 \nL 21.578125 24.515625 \nQ 13.234375 26.265625 9.515625 29.90625 \nQ 5.8125 33.546875 5.8125 39.890625 \nQ 5.8125 47.609375 11.28125 51.796875 \nQ 16.75 56 26.8125 56 \nQ 31.78125 56 36.171875 55.265625 \nQ 40.578125 54.546875 44.28125 53.078125 \nz\n\" id=\"DejaVuSans-115\"/>\n      </defs>\n      <use xlink:href=\"#DejaVuSans-71\"/>\n      <use x=\"77.490234\" xlink:href=\"#DejaVuSans-101\"/>\n      <use x=\"139.013672\" xlink:href=\"#DejaVuSans-110\"/>\n      <use x=\"202.392578\" xlink:href=\"#DejaVuSans-101\"/>\n      <use x=\"263.916016\" xlink:href=\"#DejaVuSans-114\"/>\n      <use x=\"305.029297\" xlink:href=\"#DejaVuSans-97\"/>\n      <use x=\"366.308594\" xlink:href=\"#DejaVuSans-116\"/>\n      <use x=\"405.517578\" xlink:href=\"#DejaVuSans-111\"/>\n      <use x=\"466.699219\" xlink:href=\"#DejaVuSans-114\"/>\n      <use x=\"507.8125\" xlink:href=\"#DejaVuSans-32\"/>\n      <use x=\"539.599609\" xlink:href=\"#DejaVuSans-76\"/>\n      <use x=\"593.5625\" xlink:href=\"#DejaVuSans-111\"/>\n      <use x=\"654.744141\" xlink:href=\"#DejaVuSans-115\"/>\n      <use x=\"706.84375\" xlink:href=\"#DejaVuSans-115\"/>\n     </g>\n    </g>\n    <g id=\"line2d_83\">\n     <path d=\"M 577.978125 264.420313 \nL 597.978125 264.420313 \n\" style=\"fill:none;stroke:#ff7f0e;stroke-linecap:square;stroke-width:1.5;\"/>\n    </g>\n    <g id=\"line2d_84\"/>\n    <g id=\"text_14\">\n     <!-- Discriminator Loss -->\n     <g transform=\"translate(605.978125 267.920313)scale(0.1 -0.1)\">\n      <defs>\n       <path d=\"M 19.671875 64.796875 \nL 19.671875 8.109375 \nL 31.59375 8.109375 \nQ 46.6875 8.109375 53.6875 14.9375 \nQ 60.6875 21.78125 60.6875 36.53125 \nQ 60.6875 51.171875 53.6875 57.984375 \nQ 46.6875 64.796875 31.59375 64.796875 \nz\nM 9.8125 72.90625 \nL 30.078125 72.90625 \nQ 51.265625 72.90625 61.171875 64.09375 \nQ 71.09375 55.28125 71.09375 36.53125 \nQ 71.09375 17.671875 61.125 8.828125 \nQ 51.171875 0 30.078125 0 \nL 9.8125 0 \nz\n\" id=\"DejaVuSans-68\"/>\n       <path d=\"M 9.421875 54.6875 \nL 18.40625 54.6875 \nL 18.40625 0 \nL 9.421875 0 \nz\nM 9.421875 75.984375 \nL 18.40625 75.984375 \nL 18.40625 64.59375 \nL 9.421875 64.59375 \nz\n\" id=\"DejaVuSans-105\"/>\n       <path d=\"M 48.78125 52.59375 \nL 48.78125 44.1875 \nQ 44.96875 46.296875 41.140625 47.34375 \nQ 37.3125 48.390625 33.40625 48.390625 \nQ 24.65625 48.390625 19.8125 42.84375 \nQ 14.984375 37.3125 14.984375 27.296875 \nQ 14.984375 17.28125 19.8125 11.734375 \nQ 24.65625 6.203125 33.40625 6.203125 \nQ 37.3125 6.203125 41.140625 7.25 \nQ 44.96875 8.296875 48.78125 10.40625 \nL 48.78125 2.09375 \nQ 45.015625 0.34375 40.984375 -0.53125 \nQ 36.96875 -1.421875 32.421875 -1.421875 \nQ 20.0625 -1.421875 12.78125 6.34375 \nQ 5.515625 14.109375 5.515625 27.296875 \nQ 5.515625 40.671875 12.859375 48.328125 \nQ 20.21875 56 33.015625 56 \nQ 37.15625 56 41.109375 55.140625 \nQ 45.0625 54.296875 48.78125 52.59375 \nz\n\" id=\"DejaVuSans-99\"/>\n       <path d=\"M 52 44.1875 \nQ 55.375 50.25 60.0625 53.125 \nQ 64.75 56 71.09375 56 \nQ 79.640625 56 84.28125 50.015625 \nQ 88.921875 44.046875 88.921875 33.015625 \nL 88.921875 0 \nL 79.890625 0 \nL 79.890625 32.71875 \nQ 79.890625 40.578125 77.09375 44.375 \nQ 74.3125 48.1875 68.609375 48.1875 \nQ 61.625 48.1875 57.5625 43.546875 \nQ 53.515625 38.921875 53.515625 30.90625 \nL 53.515625 0 \nL 44.484375 0 \nL 44.484375 32.71875 \nQ 44.484375 40.625 41.703125 44.40625 \nQ 38.921875 48.1875 33.109375 48.1875 \nQ 26.21875 48.1875 22.15625 43.53125 \nQ 18.109375 38.875 18.109375 30.90625 \nL 18.109375 0 \nL 9.078125 0 \nL 9.078125 54.6875 \nL 18.109375 54.6875 \nL 18.109375 46.1875 \nQ 21.1875 51.21875 25.484375 53.609375 \nQ 29.78125 56 35.6875 56 \nQ 41.65625 56 45.828125 52.96875 \nQ 50 49.953125 52 44.1875 \nz\n\" id=\"DejaVuSans-109\"/>\n      </defs>\n      <use xlink:href=\"#DejaVuSans-68\"/>\n      <use x=\"77.001953\" xlink:href=\"#DejaVuSans-105\"/>\n      <use x=\"104.785156\" xlink:href=\"#DejaVuSans-115\"/>\n      <use x=\"156.884766\" xlink:href=\"#DejaVuSans-99\"/>\n      <use x=\"211.865234\" xlink:href=\"#DejaVuSans-114\"/>\n      <use x=\"252.978516\" xlink:href=\"#DejaVuSans-105\"/>\n      <use x=\"280.761719\" xlink:href=\"#DejaVuSans-109\"/>\n      <use x=\"378.173828\" xlink:href=\"#DejaVuSans-105\"/>\n      <use x=\"405.957031\" xlink:href=\"#DejaVuSans-110\"/>\n      <use x=\"469.335938\" xlink:href=\"#DejaVuSans-97\"/>\n      <use x=\"530.615234\" xlink:href=\"#DejaVuSans-116\"/>\n      <use x=\"569.824219\" xlink:href=\"#DejaVuSans-111\"/>\n      <use x=\"631.005859\" xlink:href=\"#DejaVuSans-114\"/>\n      <use x=\"672.119141\" xlink:href=\"#DejaVuSans-32\"/>\n      <use x=\"703.90625\" xlink:href=\"#DejaVuSans-76\"/>\n      <use x=\"757.869141\" xlink:href=\"#DejaVuSans-111\"/>\n      <use x=\"819.050781\" xlink:href=\"#DejaVuSans-115\"/>\n      <use x=\"871.150391\" xlink:href=\"#DejaVuSans-115\"/>\n     </g>\n    </g>\n   </g>\n  </g>\n </g>\n <defs>\n  <clipPath id=\"p3aff99f2fc\">\n   <rect height=\"271.8\" width=\"669.6\" x=\"37.7\" y=\"7.2\"/>\n  </clipPath>\n </defs>\n</svg>\n",
      "image/png": "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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 5))\n",
    "plt.semilogy(g_loss, label=\"Generator Loss\")\n",
    "plt.semilogy(d_loss, label=\"Discriminator Loss\")\n",
    "plt.grid(True, \"both\", \"both\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### View image reconstructions\n",
    "With random latent codes view trained generator output."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 1440x576 with 10 Axes>",
      "image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n  \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n<!-- Created with matplotlib (https://matplotlib.org/) -->\n<svg height=\"444.021066pt\" version=\"1.1\" viewBox=\"0 0 1130.4 444.021066\" width=\"1130.4pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n <metadata>\n  <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\n   <cc:Work>\n    <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\n    <dc:date>2020-08-05T18:23:18.381179</dc:date>\n    <dc:format>image/svg+xml</dc:format>\n    <dc:creator>\n     <cc:Agent>\n      <dc:title>Matplotlib v3.3.0, https://matplotlib.org/</dc:title>\n     </cc:Agent>\n    </dc:creator>\n   </cc:Work>\n  </rdf:RDF>\n </metadata>\n <defs>\n  <style type=\"text/css\">*{stroke-linecap:butt;stroke-linejoin:round;}</style>\n </defs>\n <g id=\"figure_1\">\n  <g id=\"patch_1\">\n   <path d=\"M 0 444.021066 \nL 1130.4 444.021066 \nL 1130.4 0 \nL 0 0 \nz\n\" style=\"fill:none;\"/>\n  </g>\n  <g id=\"axes_1\">\n   <g clip-path=\"url(#p8dd11fa1e8)\">\n    <image height=\"193\" id=\"imagef38578cd42\" transform=\"scale(1 -1)translate(0 -193)\" width=\"193\" x=\"7.2\" xlink:href=\"data:image/png;base64,\niVBORw0KGgoAAAANSUhEUgAAAMEAAADBCAYAAAB2QtScAAAXs0lEQVR4nO2dSc8VVbSGSz32HQKCgggD1BibxJHNyIkO/AX+QUdOnDhywsSRiRo0EbEBRJDGvu+9k8v2OZXz4Nqp892bsN93tCjqVO2qc3bW+72ru27Xrl3/TP+LP/7444o5/fXXX83+5592yvT33383+/rrr994/Lrrrtv4WTvO6xA33HDDxvN5nNesHLfr2HPx/BtvvHHjcXsuXp/vlufw+BxX+79Na7XvgOfQ/vPPPzeuqXJ9+84q78KuX/lN8Dh/o7wv13nLLbdsXMPdd9/97zU33ikIBkI2QTA8VnS5dCkVVM432mDn2HE7x67J4xXK1OuW+dnff//9P4+Tepg9/7y9O1uTXaeXuhB23K5jdmUNvdfnd7larZrNNd90003N5m/966+//ndt/7mCILjGkU0QDI81OkSXwr+wTR0iKuqQfdZQUWx4L1MLKsf57DxOl0vqQqWooprwfFPeNv17EyrU0BQo+z7su+mlZ2bzmSuKU696yOvwXf/2228b1/DLL7/8e/2NVw+CgZBNEAyPlbk4czUVN2iqTq+Sw2tWjhu4frpEoyV2DmHnc22kWLfeemuzb7755mZ/8803a9e1AJnRU8ICRkaBllAvwn4HpsQRS2gYP2u0lbb+njauIAgGQjZBMDxW5iqNBhg1MrdWCcIYleoFPzsPQl3BTtAEfpb35Tu88847m33HHXc0e05/vv/++43XWrK+3qBjr7pXuVflO65QIzteUZ/s+vEEwfDIJgiGx4r/MPdlygz/IjelpeKKDRUq1RuA29Ya+LxGEfl+mMNy6NChjZ+dpmn69ddfN97D1lRR34jK+mw9le+1YvfSHkMvhaNat6Zodd01CK5BZBMEw2ONDpnaYxVVdKFruRiSM0L0qh32WcLco8FcaKWSjugNXpGG3HXXXWufYSWUVfoZep/5tttua/aePXs23vfLL79stuXhGHaCChsq6eVRh4JAkE0QDI8V3SPpDfNb9u3b1+zbb7+92XSJZ8+ebTbdaa/aQVRyhHop0BL0unfSHivyJsWYpmm65557ms3KNMspqqh1ls9ECvTII480++eff964BuY5LaGzvd/TkuBgBfEEwfDIJgiGx5o6RBXIcPr06WbT5dJVmrpSKewm7K/5Sn8hojefxfJNeimZ3ZcUiCnW83+TkpKi9Fb3kQIxb2n37t0bbapGpL/Ma1qC3u9+ST5Z5fuIJwiGRzZBMDxWpARUh5j6e+HChWb/9NNPzV6S6ktUaEalYsl6z1SCX719dypqBOmipVjPFTMqR1999VWzKz2bjJbxe921a1ezTfXje+Fxvt+dwJKcs8r5qkJWFxgE1yqyCYLhoblDDHLRplune2TOi/Xk4XEL/lA5sSLpCnpbRBrdIq7WL2jT8UoV3jyF2ZQZvusKDbVO3LwmA3NUjfh9Vxoc7ESK/E7QoeQOBYEgmyAYHitz/aQuRkuoLrz44ovNfvrpp5v9448/NvvUqVPNPn78eLNJjXgO03gr6ySMDhmtYpCK1IDPzoBgb1qxUan5+pnPQ3WIdKjSk4c2g24MivE5jT7ZfbeF3q7XvedUKu/iCYLhkU0QDI+VqRbz9oBXQPf97LPPNvupp55q9r333ttsDkNg9RldPSlHpe9OZdZYpSLMUowZUOL7sfVUcnn47D/88EOzGZScpmnau3dvs0k3P/30041rqvROIh3is1EpInj93uo2Q28wq7eBQIUWGuIJguGRTRAMj5W5VtIeKif79+9v9nPPPddsuvu33nqr2ceOHWs2qc7Fixeb3dvDx+yKakJUAltUUO67776N1/n222+bbTlCfD9ffPFFs+fBMlJJBs4YjCSdqrwv5iPxeWy+GpUvC15uq6P1kjRpokKBog4FgSCbIBgeK0v3Jegqab/yyivNJiU4d+5cs3s7GRsqHad7Ox/bYAcG+Kje3H///RuvyXfCVHPeiyoLzyEtnKZpevjhh5tN9YaqDt+1PacFyEi3SI24JoLrXpIuv6Qztp2zJNCWyrIgALIJguGxssEc5moY/KJbpju1lN5Kj5wKetOVCTvO9GE+C+kA1SE+C6kUlR8WxxM8TgVomtaDlKRAtPkZoxBUk6hA8V2Txll/qMpvgqjQlV71ZknPKVMJQ4eCAMgmCIbH2swyc4NmG6WpuMSKm6rQGwu0LSmQZ4CIlIG0xyq0vvvuu2YzQMZ1knqQUk7TNF26dKnZpFwMWM47WV9BhYaSGvF5LHBmdHNJWnVvXhCxRB1KoX0QCLIJguGhjWQqM8usoN56AVXaHhLmro329Abg7L7WVdsK5EmHLl++3GxSo+qcNSpHVIQsWMhgm70vUinem1VsXLc1QdhWMMuu05v7VUHldxBPEAyPbIJgeOhEe6McvYM2ttU7yOhZJSjW25Xa0qFJE5hTZD2XSAWNLs7fJz/P6x49erTZVJSoQFHVMQrBNVlzAcsXMiwZkEFsi2LZ8QTLgkCQTRAMj5I6ZFRkSZfiSjDLCuFJGYwakSYYvTE3zvMZOLMqNsvxYd+kSsBxmtapCOkQwWJ8o5usPuOznT9/vtlUtZg+vq2C9wqsGs4aJVS+v96+TPEEwfDIJgiGh/IZU4S2Ndur1B5P6BCVGebwkBow5ZuuvpJfZPlIpCpcG6u4SFVIPUjPLJdnmtbTtXk/qjdMpTZqZCoV3xcpU0XJ2hYqwTKiEhBN36EgWIBsgmB4rCwgVXE11ina3FGvm63k2zCtmMEfUgamJ1OxId0w+scqMypFzCliXx/SDdI2UjKC+TvTtK7Y8Nl4Px636jVSI74X9n7iWhmAs3e9JHdIlRlRISsUfMnwjgTLggDIJgiGh6pDFbezrUquXmrEHBm6UAaqqNiQGlARqRSU815UeI4cOdJsKjwW1DOla15oz95GDJbxPFIr3oPro5rE65BK8Xyjg0tmllVUIKPLlZylyojfUlD2P+8UBNc4sgmC4bGqBKoMNtfMXGVvyq0NyLC2kHT7tEmNqLKwR5BRA+vNw2dna0OeY60TSWfmwTLSAFIa0jh+xhQu2jyfz0NaVul0bXSoovwQvcXypDc2o87yjux3ScQTBMMjmyAYHiv7i9xSWSuBi97p4r3ukS6dNIM2KQoDUFR1SF1sJCvdKQNtPG4BO9IQ0jN+dp4uzQAb3wXVIbZqNGpktIEBMgYC7ZmXqH6V9GY7h785viNSROvlxO8yfYeCoIBsgmB46Myyyl//VlnWm+5qsEAK3TVHwZKWkFYcOHCg2VQRuH66U/YL4jkWULPp8VwPKRnXz7yj+bVIrajekB5Y7g3fF4d0WDdtqmOkVWb3/lZK3aGlp9XBgwebzffI74wUkbblVqWyLAiAbIJgeKg6VEljpkrTqxpVckPMvfM6dOOff/55s0kzmK5MleXQoUPNpvJj0+MtL8gK8Klk0OZ7m3eY5r9NHWI6NNdBumJ5VHwvpFhEJY2ZqFAdotKyk+t84IEHmk2KSDrE34GN+E0qdRAIsgmC4aGp1JUqIuv/Y4XqFXWFqFS6WRXYyZMnm006wFRlqkaPPfbYxjWTetBd28hXqzIjHeL581RqUhq6fqocvK4V/5Mq2IwzUiY+mxXdE73qXiU9m89FCkSb78FG+dpvzioh4wmC4ZFNEAyPVUW9sb+wzcXRTZlrss8SvT1veF8GvE6cONFs6yxNavDggw82m72DCNINUzio9DCfheskVZumdepCFYnnWd8i681k/YtsGAePV/KIDJWKM1JqBsKo6PF80iHLG7O0+OQOBYEgmyAYHlpZVqEiFmjr7QJt+S+W52OVXwSPsyUjr8+cFLY/5HG6Vut0TapDN06KxfdA103aMk3r9IbUiDTAcodImfhZPg+/V67VaG5vULNCP/hdkp7t27ev2Xx3pJ5U1hgcJf21HCedw7dxlUEwELIJguGxMpdVUY2M9hgF6sWS1GuC1IhptswRYqCGbpMVasy1ocvlcRvYwXdFCjRXh6wCzVw5z+d7ZyCQahepGxsN8F5W2G7BqcpviNfkM5OSMZDJ8605AtPobdSu5Z+FDgUBkE0QDI/Vkt4wlXGo5o6sT0wlKFRRnKxwnOrC6dOnm03aQ/rAAA5h6dwE1888IDtnmjzNmqnepDTMbSI1IhXjdc6cOdNsKirMuzIaY99ZJUfI0qTZ+GCulF3B5cuXN66Z76G3WzURTxAMj2yCYHhkEwTDY2UyZCVSaLnslsNdmXJD2NC8Je3erVaAvJPyIvk0eS3XM+8negX8O4Bcn39/zP8msJbyfB4bRMh1s3SU1+R7N9mW0Wk+gyXT2d+AvBcjww899FCzDx8+3Gy+R0qhjPhTjt5Wcl88QTA8sgmC4aGD+wjSG4NF6Qi6R01mkuMWuazIdhbxtkgk3TXnBDMpjZ+lqzeZz8ou54P7eA8+GyPd/D7sWrZuUkCr+yBM+jbKy++J72X//v3NZrIipVxSHb5fJhxahxOid05yPEEwPLIJguGx1m2iMnGkkpxUoUOmFFVUnV4loDIojjSBkWS6a7p0KkVUNfgs1i3CaMs0ecKeXdfqIEiTCD4zI8y8r0WM+QxGnxhhp1pFm2sm+LthhJx0qELNiUriZTxBMDyyCYLhsUaHKpTDSiEtSLLkuLllwpQfc4N2PqkHlSImeJEOmSpVmRDDNcwn1VgzKtIABr9IjawWgclxpBlcK2kfFa5Lly41m4oNc/lJDdkoiwE7UiBrYsZExEr3CGLJwMB4gmB4ZBMEw2NVCSZU6gnseK9tqoMFdnonoNhnbUDf2bNnm006RMpgc4J5nGtgEGlO85irxPwkBtuYS0MaQ4WH12VXBtI+3ot0hUqZKVy8F4NxpI9UvkjnSG94rwsXLjSb34GVThK9ATIiniAYHtkEwfAolVdaPo8pJJW8IDun4soqM5YttdvAc5iqTDr0xBNPNNu6U1i+kzXGmge1qPDQJrViQMqG2lmeD5UZUhqu1RqF8V4EqRppFddM2kOqQwr08ccfbzzfvr8lFCjdJoIAyCYIhofmDlWCEpVuE5Vep5UqJVN1KkPmelu8U5Wh6z516lSz50GuTfclBSI1IAW6Gh2iKkJlhvSDFIiqEz/LdfAc3ovviME1rpv3tcGAvD6/G3aJYBUf3ymDlFTZlkzLMSRYFgRANkEwPDRYVhmmVznf0qQtkGTKD10r6Qqvv2T6TSWniL1LLcWabpzrqbScn6+vMoCO79E+S+WH9yON4XNaf1NSL9I4uy+DYqSV586dazapkeUIVX5nvdQo6lAQANkEwfAoVZaZ0mJ2by8gQ2UCSqW4vlehIkgHqF5cvHix2cyvqbh0nj8PVlpwkRSF9MboKUH6xECdXZ/nM7+I6yYNo5pEFYjv6IMPPmg2FSE2ECDNXaLuVRB1KAiAbIJgeKwqeT5ERR2ygJfBpphQybAJOTY/uVc1MvC+bAXOdGb2KSI1YMCKNIR0Zl6JZj18mOeze/fuZjOl29QkS0WmksV3x/dOmkQ6xOswkEfl5/333282lTXrI1Rp/bkE6TsUBIJsgmB4lNShSj8igxXLVwb9VfoLVarbKupQhSaRMtC2gX6mdlhK+fw80hIOteO8X5vvzCCUvQtST1IvUhQGxfj9sdD+/PnzzX7vvfeaffLkyWZTBVpCgXq/71KOWtcKguAaRDZBMDxWFRqwJF/DhrqZkkH3S7dpFVu0qVJYYX5F9TIXzeNUgaj8MIhkQ0Z4nFVs07T+PLwWFSFSIL4XG2BhnZztme15GAj87LPPmv3uu+82my0sGTizgRpLfn+Vc+x5kzsUBEA2QTA8VhUFZgkqf7VTdXj00UebzSJ35u2QWtB1V1yfBc4qVXI24MNSu60CjuczcDRN65VZTNc2NY3rYDDPWj2S3lg7RNpc3yeffNLsY8eObTxOSmrr2QlU2oba+fEEwfDIJgiGxyJ1qHK+pWTb0ImXX3652W+++WazX3vttWbTXdPlWu4QYfRmSZ8i6xXEvB5WZXGdfPZpWk9dtm7dpEBWzM73TopiTQT4WapMTIFmIIy5QFTKlozX7UVvgCy5Q0EgyCYIhkep0H5J0TM/S2WCtOHo0aPNfuGFF5r9+OOPN5vulzZBt0zlw3KWGJiqVK5ZkTqvbxPjSXv4WSpAV7uWdbsmNWKgkbk6VNCY6mwdoanKHT9+vNkMkBkl66UihiUT6u2+Oqa2605BcA0imyAYHqWu1L2o5HGQKlBFIU06fPhws1966aVmv/POO82mu6aqQepilVKE5TXxs1wn05lJQ6i+8Hl5jk2tnyZ336ZekdKRDtpQDAa/SIeY9nzixIlmM0jZOztsJwrkiQrdijoUBAVkEwTDQ3OHtlXVZaBrYvotK5ZIG5555plmk6LQjetf/5ILxOtb7gzXSTrEDs08h6oJ70VFyJoDzP89D6Rteh7LSWJlGZUiBsXY/+ejjz5qNhUkBiO3VQhf6fe0LVTuFU8QDI9sgmB4rOw/lgQ9LHBh6cDMYXnjjTeaTQpEl05lhm7f+uiQPlBNMSWHx6kmWZozqRFtFsfzvlYNNv8/a41oPYKoDrFijQoP3/WHH37YbBbLmwpU6Sdl1NOwJIjW2xhCZ+x1rSAIrkFkEwTDQ+mQYVs5IDxO1/3qq682my76ySefbDZVHQ7IYGtEy8EhZaBiQypFl24jT0mHuJ4DBw5svD6vafeawwac8DipG2FBLgbLSCWZbr1EBeqdL7ZEYew93+bexRMEwyObIBge3erQttyUBaeYt0L3Rarz/PPPN9taIJJiWZWZtQO0gNrevXubzcntpGTMEaKaVFEp5p/v7frNwBZhs8Ms12hJTk5vIGxbKmSloN7uG08QDI9sgmB4rMwF9f7V3kufrA0jVYozZ840m+5uz549zaartwEUrMTiceu7w8CW0RtSIAbIGOAqpfHO3HhlBpkNyOCzEaSJ2+oObdhWLtASakQkdygICsgmCIZHKVjWO/CCMPduOUX2Fz/VHva/YfDHXLq1AzQKxBRm0h4qQgyKkQ7xs1SW+OzzKfZEpV+Sdd/mcdpMk2ZBvXWK3mlsqxi/t4otlWVBIMgmCIbHIjq0rTZ7VlxuLQNZfUa3b/2CCJuUThpC2mOzwqhQUTWyAJkNxKByNX8GWzcL5JkjxFwgVoddunSp2b05QtsqZrfze7GtYBwRTxAMj2yCYHis9R2y1N0lgZRKBVKlGsmGUVjOD2Fdpq2zNCkNVSDLF2JaNekNU6kJm1o/TVdXjjatmyDVYUE9FSFLvTbsRNfyymd7FaTKGux3Fk8QDI9sgmB4rIxO7ES3aqLi4pjbYkX0lVljBhsFe/DgwWYfOXKk2aRDzCmyyfBGI6+WAky6QmpEekObKhCVIipo1lDg/wvbCopFHQqCLSGbIBge2pWa2Im//i1HhiCdqNC2yn15nHk+pEBUe1hNxuM2FrV3iMlc6bGCfKvEs67UTJlm3lWv0tf7PEvO70XvdSxgGU8QDI9sgmB46Myy3gnhS1yiqTqW22MtCS3AZ/fiuFSOWLW+RqRD1mWaio6twY5P03ogkFSHgTA2HWCaNJsOMNdq3vn6v9Db3nAJJa0c34lRsAmWBQGQTRAMj5XN9rJBEkYtemefmTpUOX9JNRKvQ4WH1WGmCDFARqpSaZdIXK2Ynmvi/5Guca1UphgUq/QUIv4v6Y2hEojtHR5TouNdqwyCaxDZBMHwWMvbrQTOiN78IqLXrV1NUbkCo0z2XKQ07F/E4JLRCltn5dmrag2vRdXIeg0x3XynFSH77LbyeSrnL6FhUYeCAMgmCIbHGh3aiQEcve7O1BUeJ40xhcpGqfKzHLrBInoW1zO/yJSbXmXsatVj5voZwKNSdPTo0Wa//vrret3/WpM9z06rRks+20uNkkodBIJsgmB4rKzPD2mD0ZvetNxtdbquBH+McpDesKCeFWQ2hrXSHGCbhelGARnAYxtK2qSDvRRoW/lh9tnKccKUvrV0aPk+TDEk4gmC4ZFNEAyPFVUHozpGLUy9sbThimsyF2d5TfO+PZvO531JgZgjxBwcKi4MUlWmypOqVWjF/D3w/0hPSW/efvvtZr/zzjvNZjUZ12rvzpS4CtVbkvbcO++sN5BX+SzfSTxBMDyyCYLh8T+ioGWBkATq7wAAAABJRU5ErkJggg==\" y=\"-6.613793\"/>\n   </g>\n  </g>\n  <g id=\"axes_2\">\n   <g clip-path=\"url(#p87c80878c8)\">\n    <image height=\"193\" id=\"imagea26df1f2c8\" transform=\"scale(1 -1)translate(0 -193)\" width=\"193\" x=\"238.096552\" xlink:href=\"data:image/png;base64,\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\" y=\"-6.613793\"/>\n   </g>\n  </g>\n  <g id=\"axes_3\">\n   <g clip-path=\"url(#p2a39d3380b)\">\n    <image height=\"193\" id=\"imagebe40b8aa70\" transform=\"scale(1 -1)translate(0 -193)\" width=\"193\" x=\"468.993103\" xlink:href=\"data:image/png;base64,\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\" y=\"-6.613793\"/>\n   </g>\n  </g>\n  <g id=\"axes_4\">\n   <g clip-path=\"url(#p056e7b2292)\">\n    <image height=\"193\" id=\"image5fbbcd8e86\" transform=\"scale(1 -1)translate(0 -193)\" width=\"193\" x=\"699.889655\" xlink:href=\"data:image/png;base64,\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\" y=\"-6.613793\"/>\n   </g>\n  </g>\n  <g id=\"axes_5\">\n   <g clip-path=\"url(#p36d6b3e236)\">\n    <image height=\"193\" id=\"image6a278c2b2e\" transform=\"scale(1 -1)translate(0 -193)\" width=\"193\" x=\"930.786207\" xlink:href=\"data:image/png;base64,\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\" y=\"-6.613793\"/>\n   </g>\n  </g>\n  <g id=\"axes_6\">\n   <g clip-path=\"url(#p9e49c69866)\">\n    <image height=\"193\" id=\"image5f66dae4a0\" transform=\"scale(1 -1)translate(0 -193)\" width=\"193\" x=\"7.2\" xlink:href=\"data:image/png;base64,\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\" y=\"-243.821066\"/>\n   </g>\n  </g>\n  <g id=\"axes_7\">\n   <g clip-path=\"url(#pb62119b4d5)\">\n    <image height=\"193\" id=\"image546263cae6\" transform=\"scale(1 -1)translate(0 -193)\" width=\"193\" x=\"238.096552\" xlink:href=\"data:image/png;base64,\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\" y=\"-243.821066\"/>\n   </g>\n  </g>\n  <g id=\"axes_8\">\n   <g clip-path=\"url(#p912fd50499)\">\n    <image height=\"193\" id=\"image474004b5b9\" transform=\"scale(1 -1)translate(0 -193)\" width=\"193\" x=\"468.993103\" xlink:href=\"data:image/png;base64,\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\" y=\"-243.821066\"/>\n   </g>\n  </g>\n  <g id=\"axes_9\">\n   <g clip-path=\"url(#p4a5f2d5c77)\">\n    <image height=\"193\" id=\"image5fc508d902\" transform=\"scale(1 -1)translate(0 -193)\" width=\"193\" x=\"699.889655\" xlink:href=\"data:image/png;base64,\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\" y=\"-243.821066\"/>\n   </g>\n  </g>\n  <g id=\"axes_10\">\n   <g clip-path=\"url(#pa069cefbe4)\">\n    <image height=\"193\" id=\"image504e749f9d\" transform=\"scale(1 -1)translate(0 -193)\" width=\"193\" x=\"930.786207\" xlink:href=\"data:image/png;base64,\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\" y=\"-243.821066\"/>\n   </g>\n  </g>\n </g>\n <defs>\n  <clipPath id=\"p8dd11fa1e8\">\n   <rect height=\"192.413793\" width=\"192.413793\" x=\"7.2\" y=\"7.2\"/>\n  </clipPath>\n  <clipPath id=\"p87c80878c8\">\n   <rect height=\"192.413793\" width=\"192.413793\" x=\"238.096552\" y=\"7.2\"/>\n  </clipPath>\n  <clipPath id=\"p2a39d3380b\">\n   <rect height=\"192.413793\" width=\"192.413793\" x=\"468.993103\" y=\"7.2\"/>\n  </clipPath>\n  <clipPath id=\"p056e7b2292\">\n   <rect height=\"192.413793\" width=\"192.413793\" x=\"699.889655\" y=\"7.2\"/>\n  </clipPath>\n  <clipPath id=\"p36d6b3e236\">\n   <rect height=\"192.413793\" width=\"192.413793\" x=\"930.786207\" y=\"7.2\"/>\n  </clipPath>\n  <clipPath id=\"p9e49c69866\">\n   <rect height=\"192.413793\" width=\"192.413793\" x=\"7.2\" y=\"244.407273\"/>\n  </clipPath>\n  <clipPath id=\"pb62119b4d5\">\n   <rect height=\"192.413793\" width=\"192.413793\" x=\"238.096552\" y=\"244.407273\"/>\n  </clipPath>\n  <clipPath id=\"p912fd50499\">\n   <rect height=\"192.413793\" width=\"192.413793\" x=\"468.993103\" y=\"244.407273\"/>\n  </clipPath>\n  <clipPath id=\"p4a5f2d5c77\">\n   <rect height=\"192.413793\" width=\"192.413793\" x=\"699.889655\" y=\"244.407273\"/>\n  </clipPath>\n  <clipPath id=\"pa069cefbe4\">\n   <rect height=\"192.413793\" width=\"192.413793\" x=\"930.786207\" y=\"244.407273\"/>\n  </clipPath>\n </defs>\n</svg>\n",
      "image/png": "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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "test_img_count = 10\n",
    "test_latents = default_make_latent(test_img_count, latent_size).to(device)\n",
    "fakes = gen_net(test_latents)\n",
    "\n",
    "fig, axs = plt.subplots(2, (test_img_count // 2), figsize=(20, 8))\n",
    "axs = axs.flatten()\n",
    "for i, ax in enumerate(axs):\n",
    "    ax.axis(\"off\")\n",
    "    ax.imshow(fakes[i, 0].cpu().data.numpy(), cmap=\"gray\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cleanup data directory\n",
    "\n",
    "Remove directory if a temporary was used."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "pycharm": {
     "is_executing": true
    }
   },
   "outputs": [],
   "source": [
    "if directory is None:\n",
    "    shutil.rmtree(root_dir)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
